diff --git a/pydata-tel-avid-2022/category.json b/pydata-tel-avid-2022/category.json
new file mode 100644
index 000000000..b9ab9f625
--- /dev/null
+++ b/pydata-tel-avid-2022/category.json
@@ -0,0 +1,3 @@
+{
+  "title": "PyData Tel Avid 2022"
+}
diff --git a/pydata-tel-avid-2022/videos/adi-watzman-causal-machine-learning-whats-in-it-for-data-scientists-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/adi-watzman-causal-machine-learning-whats-in-it-for-data-scientists-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..571d77cf2
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/adi-watzman-causal-machine-learning-whats-in-it-for-data-scientists-pydata-tel-aviv-2022.json
@@ -0,0 +1,55 @@
+{
+  "description": "Lightning Talk \n\n**Causal ML** brings ML practitioners exciting opportunities to go beyond correlation, with success stories in multiple big tech companies. However, being rooted in the theory of traditional Causal Inference, Causal ML is still less accessible to data scientists who are already juggling to master numerous sub-fields. In this talk we will walk a first step to bridge this gap, by exploring the rich landscape of Causal ML from the data scientist perspective, focusing on \u201cwhat\u2019s in it for us\u201d and which practical tools can be used.\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 338,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/ZTfd-yzphU8/maxresdefault.jpg",
+  "title": "Adi Watzman: Causal Machine Learning \u2013 What\u2019s in it for Data Scientists? | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=ZTfd-yzphU8"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/aleksander-molak-uri-itai-flexibility-general-average-for-ml-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/aleksander-molak-uri-itai-flexibility-general-average-for-ml-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..a0b6d4674
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/aleksander-molak-uri-itai-flexibility-general-average-for-ml-pydata-tel-aviv-2022.json
@@ -0,0 +1,59 @@
+{
+  "description": "From summarizing distributions to pooling operators and measuring the goodness of fit, averaging plays a unique and universally recognized role in the field of machine learning. In the talk we present Generalized Average (GA) - a continuous and fully differentiable average operator that allows for flexible interpolation between min, max and three different types of averages: arithmetic, geometric and harmonic. We share the results of two lines of experiments: (1) using GA in hyperparameter tuning for false-positive-averse cases (e.g. fraud detection) and (2) using GA as a pooling operator in Graph Attention Networks to improve the model\u2019s flexibility. Finally, we present an open-source Python package with our implementation of GA. The talk is addressed to machine learning practitioners, who are interested in enriching their toolbox.\n\nSlides: https://drive.google.com/file/d/1aESVbNFytU8gj3lCvxUx4YEuAVkPyfRD\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 1884,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://drive.google.com/file/d/1aESVbNFytU8gj3lCvxUx4YEuAVkPyfRD",
+      "url": "https://drive.google.com/file/d/1aESVbNFytU8gj3lCvxUx4YEuAVkPyfRD"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/R7R0-Fh2Tb8/maxresdefault.jpg",
+  "title": "Aleksander Molak & Uri Itai: Flexibility General Average for ML| PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=R7R0-Fh2Tb8"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/anna-roitberg-distant-annotation-for-training-data-preparation-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/anna-roitberg-distant-annotation-for-training-data-preparation-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..b730c9b0d
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/anna-roitberg-distant-annotation-for-training-data-preparation-pydata-tel-aviv-2022.json
@@ -0,0 +1,59 @@
+{
+  "description": "Lightning Talk \n\nDistant Annotation (aka Distant Supervision) is an annotation method that allows training data to be labeled automatically. It has become the standard method for relation extraction tasks. The method utilizes an existing database, such as Freebase, Wikipedia, or a domain-specific database, to collect examples for the relations we want to extract.\n\nSlides: https://drive.google.com/file/d/1AkDFM5EK33XcXdZWa9QQyiKelbXwQ1wI\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 308,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://drive.google.com/file/d/1AkDFM5EK33XcXdZWa9QQyiKelbXwQ1wI",
+      "url": "https://drive.google.com/file/d/1AkDFM5EK33XcXdZWa9QQyiKelbXwQ1wI"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/teaAW18XeXI/maxresdefault.jpg",
+  "title": "Anna Roitberg: Distant Annotation for Training Data Preparation | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=teaAW18XeXI"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/avishai-barnoy-deepcook-code-your-way-through-everyday-chores-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/avishai-barnoy-deepcook-code-your-way-through-everyday-chores-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..e1a4d7ac5
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/avishai-barnoy-deepcook-code-your-way-through-everyday-chores-pydata-tel-aviv-2022.json
@@ -0,0 +1,59 @@
+{
+  "description": "Lightning Talk \n\nThis lecture will present a side project focused on automating a daily task I have been struggling with. I hate choosing what to eat, so I combined my coding hobby with some data I structured to build a dinner-idea suggestion system. I designed the features I needed and learned how to structure a code in a readable way. By structuring the code in an extensible way I made it easier to extend the program to new interfaces, right now having both a CLI and a Streamlit web app that use the same core functions.\n\nSlides: https://docs.google.com/presentation/d/13rES1eqhc4ejmPzoxt36M9bITnWKDdgm\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 305,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://docs.google.com/presentation/d/13rES1eqhc4ejmPzoxt36M9bITnWKDdgm",
+      "url": "https://docs.google.com/presentation/d/13rES1eqhc4ejmPzoxt36M9bITnWKDdgm"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/OJPgN_ce23U/maxresdefault.jpg",
+  "title": "Avishai Barnoy: DeepCook: Code Your Way Through Everyday Chores | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=OJPgN_ce23U"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/aviv-zaken-simple-data-processing-pipeline-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/aviv-zaken-simple-data-processing-pipeline-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..b002e7fb0
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/aviv-zaken-simple-data-processing-pipeline-pydata-tel-aviv-2022.json
@@ -0,0 +1,59 @@
+{
+  "description": "Lightning Talk \n\nIntroducing a technique from the DevOps world for configuring pipelines for processing data of various (and different) formats, characteristics and noise in a generic and easy way.\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nSlides: https://drive.google.com/file/d/152H7rWuzOQz23gfG13q6AVJ8JIf6pW1T\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 266,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://drive.google.com/file/d/152H7rWuzOQz23gfG13q6AVJ8JIf6pW1T",
+      "url": "https://drive.google.com/file/d/152H7rWuzOQz23gfG13q6AVJ8JIf6pW1T"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/kHLZR_qvluk/maxresdefault.jpg",
+  "title": "Aviv Zaken: Simple Data Processing Pipeline | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=kHLZR_qvluk"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/cheuk-ting-ho-i-hate-writing-tests-that-s-why-i-use-hypothesis-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/cheuk-ting-ho-i-hate-writing-tests-that-s-why-i-use-hypothesis-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..fd8ac7827
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/cheuk-ting-ho-i-hate-writing-tests-that-s-why-i-use-hypothesis-pydata-tel-aviv-2022.json
@@ -0,0 +1,55 @@
+{
+  "description": "In this talk, we will explore what is property-based testing and why it can do a lot of heavy lifting in writing tests for us. As a contributor, I will introduce Hypothesis, a Python library that can help perform property-based tests with ease.\n\nAt the start of the talk, we will understand the power of property-based tests, what is it, how is it different from what we \u201cnormally do\u201d - testing by example, and why is it useful in testing our code. This will be followed by demonstrations using Hypothesis. With a few examples, we will have a glimpse of how to create strategies - recipes for describing the test data you want to generate.\n\nAfter that, we will also explore the Ghostwriters in Hypothesis which will actually write the test for you.\n\nThis talk is for Pythonistas who are new to property-based testing and found thinking of what parameters to use for testing a difficult task. This talk may provide them with a new approach to writing tests, which will be more efficient for some cases.\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 1794,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/__DfM6R4nVs/maxresdefault.jpg",
+  "title": "Cheuk Ting Ho: I Hate writing Tests, That's Why I Use Hypothesis | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=__DfM6R4nVs"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/dimitry-venger-extreme-value-analysis-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/dimitry-venger-extreme-value-analysis-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..812f56921
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/dimitry-venger-extreme-value-analysis-pydata-tel-aviv-2022.json
@@ -0,0 +1,59 @@
+{
+  "description": "How do you use data from 15 years of observations to predict the magnitude of a \u201conce in 50 years\u201d storm? How can we build a network infrastructure that can handle the maximum traffic over a decade, using just one year of data?\nExtreme value Analysis (EVA) provides a statistical and technical framework for the analysis of extreme deviation from the median of probability distributions. It is used in multiple fields to predict the probability of the recurrence of extreme outliers in data or even of the occurrence of heretofore unobserved phenomena.\nThis talk aims to provide the listener with a basic understanding of the analysis framework and the mathematical justification for its correctness. Numerous alternative routes, pitfalls and decision points encountered during analysis will be presented.\nCurrently, available libraries in Python allow only very rudimentary EVA, and many useful and sometimes necessary operations lack implementations. So while this talk is aimed at people hearing about EVA for the first time, it is also a call for contributors to implement those necessary features.\n\nSlides: https://docs.google.com/presentation/d/1KB2F2Q-8y8SNyDCWZNZnGcJEJI1oRf5x\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 1914,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://docs.google.com/presentation/d/1KB2F2Q-8y8SNyDCWZNZnGcJEJI1oRf5x",
+      "url": "https://docs.google.com/presentation/d/1KB2F2Q-8y8SNyDCWZNZnGcJEJI1oRf5x"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/7XpZjt8cvgs/maxresdefault.jpg",
+  "title": "Dimitry Venger - Extreme Value Analysis | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=7XpZjt8cvgs"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/dina-bavli-life-death-and-shopping-he-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/dina-bavli-life-death-and-shopping-he-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..9fe8f3a08
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/dina-bavli-life-death-and-shopping-he-pydata-tel-aviv-2022.json
@@ -0,0 +1,59 @@
+{
+  "description": "When dealing with survival analysis, the model's success is predicting death correctly. But it can also predict an engine failure, abandonment, or even purchases.\nIn purchase prediction, survival analysis, or churn prediction, the data is usually labeled or artificially labeled by a set of rules- such as inactivity for 30 days equivalent to churn. But the data structure is different from classical machine learning, and the data handling and modeling are different accordingly.\nIn this lecture, we will cover the data structures and aggregations for such analysis focusing on time aggregations using PySpark and what NLP got to do with any of it.\n\nSlides: https://docs.google.com/presentation/d/1AP08NgPga--cuVu8Ao12aPTSv0ex0MCeG2Ksnkavlw8\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 1639,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://docs.google.com/presentation/d/1AP08NgPga--cuVu8Ao12aPTSv0ex0MCeG2Ksnkavlw8",
+      "url": "https://docs.google.com/presentation/d/1AP08NgPga--cuVu8Ao12aPTSv0ex0MCeG2Ksnkavlw8"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/ujUOzViCuvo/maxresdefault.jpg",
+  "title": "Dina Bavli: Life, Death, and Shopping (HE) | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=ujUOzViCuvo"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/efrat-garber-aran-my-family-and-other-startups-he-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/efrat-garber-aran-my-family-and-other-startups-he-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..51e494cc7
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/efrat-garber-aran-my-family-and-other-startups-he-pydata-tel-aviv-2022.json
@@ -0,0 +1,55 @@
+{
+  "description": "Lightning Talk \n\nAn amusing and thought provoking spoken word about parenting, High Tech, data and profits.\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 272,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/kgaDPoYe-BE/maxresdefault.jpg",
+  "title": "Efrat Garber Aran: My Family and Other Startups (HE)  | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=kgaDPoYe-BE"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/hilla-deleon-over-and-under-estimation-of-vaccine-effectiveness-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/hilla-deleon-over-and-under-estimation-of-vaccine-effectiveness-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..d30c86c24
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/hilla-deleon-over-and-under-estimation-of-vaccine-effectiveness-pydata-tel-aviv-2022.json
@@ -0,0 +1,59 @@
+{
+  "description": "Does the indirect protection of the vaccine biases vaccine effectiveness (VE) estimations?\n\nSARS-CoV-2 vaccines provide high protection against infection to the vaccinated individual and indirect protection to its surroundings by blocking further transmission. Divergent results have been reported on the effectiveness of the SARS-CoV-2 vaccines. Here, we argue that this divergence is because the analyses did not consider indirect protection. Using a novel heterogeneous infection model (python) and real-world data, we demonstrate that heterogeneous vaccination rates among families and communities, both spatially and temporally, and the study design that is used may significantly skew the VE estimations\n\nSlides: https://docs.google.com/presentation/d/1WJ0xc_k-tmK65J194RDjYt3R7wc1XM86\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 1491,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://docs.google.com/presentation/d/1WJ0xc_k-tmK65J194RDjYt3R7wc1XM86",
+      "url": "https://docs.google.com/presentation/d/1WJ0xc_k-tmK65J194RDjYt3R7wc1XM86"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/WcIczCxcH2g/maxresdefault.jpg",
+  "title": "Hilla Deleon: Over- and Under-Estimation of Vaccine Effectiveness  | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=WcIczCxcH2g"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/liron-faybish-keeping-sensitive-data-safe-using-recommendation-systems-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/liron-faybish-keeping-sensitive-data-safe-using-recommendation-systems-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..c44c444f2
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/liron-faybish-keeping-sensitive-data-safe-using-recommendation-systems-pydata-tel-aviv-2022.json
@@ -0,0 +1,59 @@
+{
+  "description": "What if I told you every-day recommendation systems can be utilized to detect unwanted behaviors? Now, what if I told you they can also be harnessed to prevent internal security violations in organizations? Well, It\u2019s happening. Kind of neat, right?\n\nSlides:  https://docs.google.com/presentation/d/1LordioOpIelVy8eWpi8I14HFAlZ64HKV\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 1549,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://docs.google.com/presentation/d/1LordioOpIelVy8eWpi8I14HFAlZ64HKV",
+      "url": "https://docs.google.com/presentation/d/1LordioOpIelVy8eWpi8I14HFAlZ64HKV"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/WFr4PP0eRXw/maxresdefault.jpg",
+  "title": "Liron Faybish: Keeping Sensitive Data Safe Using Recommendation Systems | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=WFr4PP0eRXw"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/matar-haller-noam-levy-constructing-querying-data-model-for-online-harm-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/matar-haller-noam-levy-constructing-querying-data-model-for-online-harm-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..7c5f469d5
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/matar-haller-noam-levy-constructing-querying-data-model-for-online-harm-pydata-tel-aviv-2022.json
@@ -0,0 +1,55 @@
+{
+  "description": "One of the biggest challenges facing online platforms today and especially those with user-generated content is detecting harmful content and malicious behavior. One of the reasons harmful content detection is so challenging is that it is a multidimensional problem. Items can be in any number of formats (video, text, image, and audio), any language, and violative in any number of ways, from extreme gore and hate to suggestive or ambiguous nudity or bullying, and are uploaded or shared by a myriad of users (some of which are trying to circumvent being banned).\n\nIn order to be able to build algorithms that analyze and detect this harmful activity at scale, we need a data model that can capture the complexities of this online ecosystem. In this talk, we will discuss how ActiveFence models the online content, media, creators, and users that interact with the content with likes, shares, or comments. Modeling the relationships between these items yields a complex connected graph, and in order to calculate a score that accurately reflects the probability of harm, we need to be able to query and access all of the relations of any given item. We will dive into the details of the complex and adversarial online space, the ActiveFence data model, and how we abstract the complexity of querying a graph-like data model using traditional SQL PySpark queries to provide maximum value to our algorithms.\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 1810,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/BMVl9LjotJg/maxresdefault.jpg",
+  "title": "Matar Haller & Noam Levy: Constructing & Querying Data Model for Online Harm  | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=BMVl9LjotJg"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/nir-barazida-notebook-to-production-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/nir-barazida-notebook-to-production-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..f9e475e29
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/nir-barazida-notebook-to-production-pydata-tel-aviv-2022.json
@@ -0,0 +1,59 @@
+{
+  "description": "Jupyter Notebooks have seen enthusiastic adoption among the data science community to become the default environment for research.\n\nBut, are Jupyter Notebooks really the best home for data scientists to develop production-ready projects? The non-linear workflow, lack of versioning capabilities, no IDE integration, and inadequate debugging tools make it laborious to productionize a project created in a Jupyter Notebook environment.\n\nShould we just throw our Jupyter Notebooks out the window and move to classic IDEs? Probably not \u2013 Jupyter Notebooks are, after all, a great tool that gives us superhuman abilities. We can, however, be more production-oriented when using them. How does this look in practice? That is exactly what we'll cover in this talk.\n\nSlides: https://docs.google.com/presentation/d/1pJPB2cBcM0AQ7lasNTVGQ2Ya9KpfKBmK\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 1631,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://docs.google.com/presentation/d/1pJPB2cBcM0AQ7lasNTVGQ2Ya9KpfKBmK",
+      "url": "https://docs.google.com/presentation/d/1pJPB2cBcM0AQ7lasNTVGQ2Ya9KpfKBmK"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/8vjoHWCYQYk/maxresdefault.jpg",
+  "title": "Nir Barazida: Notebook To Production | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=8vjoHWCYQYk"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/rachel-shalom-gans-the-case-of-predictive-business-process-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/rachel-shalom-gans-the-case-of-predictive-business-process-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..0a7cc1910
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/rachel-shalom-gans-the-case-of-predictive-business-process-pydata-tel-aviv-2022.json
@@ -0,0 +1,59 @@
+{
+  "description": "Generative Adversarial Networks (GANs) are a type of unsupervised learning that are well known for their ability to generate new images, videos or text, but they can also be used for a wider range of use-cases.\nIn this talk I will present how we used GANs at Dell for predicting the user's next activities on Dell\u2019s website, and also cover the fundamentals of GANs, for those less familiar with it and its various applications. You should join this talk if you want to learn the basics of GANs and a less conventional way to use it for a business use-case.\n\nSlides: https://docs.google.com/presentation/d/1-eX_Vx_6Y196qwkZksamCXABrUh85RtW-nLGkMd9F4g\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 1750,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://docs.google.com/presentation/d/1-eX_Vx_6Y196qwkZksamCXABrUh85RtW-nLGkMd9F4g",
+      "url": "https://docs.google.com/presentation/d/1-eX_Vx_6Y196qwkZksamCXABrUh85RtW-nLGkMd9F4g"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/tuxCGQKFqas/maxresdefault.jpg",
+  "title": "Rachel Shalom: GANs: The Case of Predictive Business Process | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=tuxCGQKFqas"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/racheli-abo-data-sampling-using-data-maps-he-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/racheli-abo-data-sampling-using-data-maps-he-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..f5a6a3624
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/racheli-abo-data-sampling-using-data-maps-he-pydata-tel-aviv-2022.json
@@ -0,0 +1,59 @@
+{
+  "description": "When gathering data to train a ML model, the common belief is \u2018the more the merrier\u2019. In reality though, individual data samples may have varying effects on the learning process. How can we automatically measure the contribution of samples towards learning, and what can we do with it?\n\nSlides: https://docs.google.com/presentation/d/1c2QVbrT9ajJhrnvQ1hmaU19xYoa7sjoC\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 1566,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://docs.google.com/presentation/d/1c2QVbrT9ajJhrnvQ1hmaU19xYoa7sjoC",
+      "url": "https://docs.google.com/presentation/d/1c2QVbrT9ajJhrnvQ1hmaU19xYoa7sjoC"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/1hMxMcS77Lk/maxresdefault.jpg",
+  "title": "Racheli Abo:  Data Sampling Using Data Maps (HE) |  PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=1hMxMcS77Lk"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/raymond-hettinger-numerical-marvels-inside-python-keynote-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/raymond-hettinger-numerical-marvels-inside-python-keynote-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..86702523a
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/raymond-hettinger-numerical-marvels-inside-python-keynote-pydata-tel-aviv-2022.json
@@ -0,0 +1,59 @@
+{
+  "description": "Bio:\nRaymond has been a prolific contributor to the CPython project for over a decade, having implemented and maintained many of Python's great features. He has been instrumental in modules like bisect, collections, decimal, functools, itertools, math, random, with types like namedtuple, sets, dictionaries, and in many other places around the codebase. He has contributed to the modification of nearly 90,000 lines of code in the CPython repository, and has made over 160 changes in the PEP repository.\n\nNotebooks: https://drive.google.com/file/d/1SXtqtQXJj9Pg5Kl9Z2eXGcnDfa7oy89d\n\nRaymond has also served as a director of the Python Software Foundation, and has mentored many people over the years on their contributions to the python-dev community. He's also well known for his contributions to the Python Cookbook, and shares many pieces of Python wisdom on Twitter. He received the Distinguished Service Award at PyCon 2014 for his exceptional contributions to the python community.\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 2950,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://drive.google.com/file/d/1SXtqtQXJj9Pg5Kl9Z2eXGcnDfa7oy89d",
+      "url": "https://drive.google.com/file/d/1SXtqtQXJj9Pg5Kl9Z2eXGcnDfa7oy89d"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/wiGkV37Kbxk/maxresdefault.jpg",
+  "title": "Raymond Hettinger: Numerical Marvels Inside Python - Keynote | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=wiGkV37Kbxk"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/roy-kishony-quibbler-your-data-interactive-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/roy-kishony-quibbler-your-data-interactive-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..3493eb92e
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/roy-kishony-quibbler-your-data-interactive-pydata-tel-aviv-2022.json
@@ -0,0 +1,59 @@
+{
+  "description": "https://github.com/Technion-Kishony-lab/quibbler\n\nAn open-source package for interactive, reproducible and efficient data analytics.\n\nInteractivity, reproducibility and efficiency are becoming increasingly important, yet challenging, in today\u2019s data-rich applications. Inevitably, data analysis pipelines are often heavily parametrized, and we lack effective ways to play with parameters and understand how they affect focal downstream results. In the talk, we introduce \u201cQuibbler\u201d - a new open-source, pure-python package for building inherently interactive, yet traceable, transparent and efficient data analysis applications. Founded on a data-flow paradigm, Quibbler allows processing data through any series of analysis steps, while automatically tracking functional relationships between downstream results and upstream parameters. Quibbler facilitates and embraces human interventions as an inherent part of the analysis pipeline: input parameters, as well as algorithmic exceptions, can be specified interactively, and any such interventions are automatically recorded and documented. Changes to upstream parameters propagate downstream, pinpointing which specific data items, or even specific elements thereof, are affected, thereby vastly saving unnecessary recalculations. Quibbler, therefore, facilitates hands-on interactions with data in ways that are not only flexible, fun and interactive, but also traceable, reproducible, and computationally efficient.\n\nAnd most importantly, to get started you do not need to learn any new syntax: with Quibbler your standard Python analysis code is automatically live and interactive!\n\nWe are just launching Quibbler as an open-source project, and are eager to see it being used and integrated within a range of data science applications. We are of course also looking for any feedback, suggestions and help.\n\nHappy quibbling!\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 2135,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://github.com/Technion-Kishony-lab/quibbler",
+      "url": "https://github.com/Technion-Kishony-lab/quibbler"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/euGnxrmBkEY/maxresdefault.jpg",
+  "title": "Roy Kishony: Quibbler: Your Data - Interactive! | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=euGnxrmBkEY"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/tal-erez-hauer-unleash-big-data-clustering-he-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/tal-erez-hauer-unleash-big-data-clustering-he-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..947a12da6
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/tal-erez-hauer-unleash-big-data-clustering-he-pydata-tel-aviv-2022.json
@@ -0,0 +1,59 @@
+{
+  "description": "I was about to give up my DBSCAN clustering solution when I found out how long it takes to train it with 400 million records. The density-based clustering algorithm was exactly what we needed at PayPal to solve a few unsupervised anomaly-detection problems, but when runtime hits O(n^2) it just seemed impossible.\n\nThe talk will introduce how we re-implemented DBSCAN for big data by parallelizing it using a graph algorithm, and walk through our solution which enables clustering of 400M records in a few hours.\n\nSlides: https://docs.google.com/presentation/d/1Wg5I7GN818H-JayNPxZiD664A3sfzaOc\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 1587,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://docs.google.com/presentation/d/1Wg5I7GN818H-JayNPxZiD664A3sfzaOc",
+      "url": "https://docs.google.com/presentation/d/1Wg5I7GN818H-JayNPxZiD664A3sfzaOc"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/9dqhx3dUA7s/maxresdefault.jpg",
+  "title": "Tal Erez Hauer: Unleash Big Data Clustering (HE) | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=9dqhx3dUA7s"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/tsvi-lev-or-katz-synthetic-data-in-vision-ai-theory-and-practice-he-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/tsvi-lev-or-katz-synthetic-data-in-vision-ai-theory-and-practice-he-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..fdaa05e64
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/tsvi-lev-or-katz-synthetic-data-in-vision-ai-theory-and-practice-he-pydata-tel-aviv-2022.json
@@ -0,0 +1,59 @@
+{
+  "description": "Synthethic Data Generation is now a popular and important addition to standard image augmentation methods and real life data acquisition and labeling. We will show how the unique, metadata-driven nature of synthetic data pipelines enables new method to improve AI explainability, accuracy and training times\n\nSlides: https://drive.google.com/file/d/1dbyzJMHklO7o2WxqzGILowDFgQhwoS54\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 1722,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
+    },
+    {
+      "label": "https://www.linkedin.com/company/17907513",
+      "url": "https://www.linkedin.com/company/17907513"
+    },
+    {
+      "label": "https://www.meetup.com/PyData-Tel-Aviv/",
+      "url": "https://www.meetup.com/PyData-Tel-Aviv/"
+    },
+    {
+      "label": "https://twitter.com/PyDataTLV",
+      "url": "https://twitter.com/PyDataTLV"
+    },
+    {
+      "label": "https://drive.google.com/file/d/1dbyzJMHklO7o2WxqzGILowDFgQhwoS54",
+      "url": "https://drive.google.com/file/d/1dbyzJMHklO7o2WxqzGILowDFgQhwoS54"
+    },
+    {
+      "label": "https://www.facebook.com/PyDataTLV",
+      "url": "https://www.facebook.com/PyDataTLV"
+    }
+  ],
+  "speakers": [
+    "TODO"
+  ],
+  "tags": [
+    "Education",
+    "Julia",
+    "NumFOCUS",
+    "Opensource",
+    "PyData",
+    "Python",
+    "Tutorial",
+    "coding",
+    "how to program",
+    "learn",
+    "learn to code",
+    "python 3",
+    "scientific programming",
+    "software"
+  ],
+  "thumbnail_url": "https://i.ytimg.com/vi/8uXAjkdOjCY/maxresdefault.jpg",
+  "title": "Tsvi Lev & Or Katz: Synthetic Data in Vision AI: Theory and Practice (HE) | PyData Tel Aviv 2022",
+  "videos": [
+    {
+      "type": "youtube",
+      "url": "https://www.youtube.com/watch?v=8uXAjkdOjCY"
+    }
+  ]
+}
diff --git a/pydata-tel-avid-2022/videos/yoel-shuki-breaking-the-privacy-utility-tradeoff-with-deming-regression-he-pydata-tel-aviv-2022.json b/pydata-tel-avid-2022/videos/yoel-shuki-breaking-the-privacy-utility-tradeoff-with-deming-regression-he-pydata-tel-aviv-2022.json
new file mode 100644
index 000000000..ca83c2448
--- /dev/null
+++ b/pydata-tel-avid-2022/videos/yoel-shuki-breaking-the-privacy-utility-tradeoff-with-deming-regression-he-pydata-tel-aviv-2022.json
@@ -0,0 +1,55 @@
+{
+  "description": "Yoel Zeldes & Shuki Cohen\n\nImagine you\u2019re conducting a salary survey with the goal of training a model to predict the salary. Cool, right? Not if you don\u2019t handle user privacy\u2026 How can we make sure the collected data can\u2019t be used to identify the users, while still being able to properly train our model?\n\nIn this session, we\u2019ll eat the cake and leave it whole: We\u2019ll use a less known model called Deming regression to handle our anonymized data, and it\u2019ll have a quality similar to a model trained on the private data! And all will be live coded, starting with an empty Jupyter notebook. Join the fun ;)\n\nFollow PyData Tel Aviv on:\nhttps://www.meetup.com/PyData-Tel-Aviv/\nhttps://www.linkedin.com/company/17907513\nhttps://www.facebook.com/PyDataTLV\nhttps://twitter.com/PyDataTLV\n\nwww.pydata.org\n\nPyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.",
+  "duration": 1470,
+  "language": "eng",
+  "recorded": "2022-12-13",
+  "related_urls": [
+    {
+      "label": "Conference Website",
+      "url": "https://pydata.org/telaviv2022/"
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