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AceleraDev DS References

Modulo 1

An Introduction to Statistical Learning with Applications in R Python Data Science Handbook DATA MINING AND ANALYSIS Fundamental Concepts and Algorithms - Book Download

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Repositório do programa Minimally Sufficient Pandas Why and How to Use Pandas with Large Data Getting started with Data Analysis with Python Pandas Python Pandas: Tricks & Features You May Not Know Essential Basic Functionality Pandas Tutorial: Essentials of Data Science in Pandas Library Python Pandas Tutorial: A Complete Introduction for Beginners Basic Time Series Manipulation with Pandas Tidy Data Python For Data Science - Cheat Sheet Pandas Basics

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How to self-learn statistics of data science Statistics Done Wrong Exploratory Data Analysis | R for Data Science xploratory Data Analysis A Gentle Introduction to Exploratory Data Analysis A Simple Tutorial on Exploratory Data Analysis Introduction to Hypothesis Testing The Power of Visualization in Data Science 15 Stunning Data Visualizations (And What You Can Learn From Them) 15 Insane Things That Correlate With Each Other

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Probability Theory Review for Machine Learning Understanding Probability Distributions Probability Distribution Statistical Modeling: The Two Cultures Variáveis Aleatórias Unidimensionais Probability and Information Theory

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A Gentle Introduction to Statistical Hypothesis Testing How to Correctly Interpret P Values A Dirty Dozen: Twelve P-Value Misconceptions An investigation of the false discovery rate and the misinterpretation of p-values Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations Why Are P Values Misinterpreted So Frequently? Statistical Significance Explained Definition of Power The Math Behind A/B Testing with Example Python Code Handy Functions for A/B Testing in Python

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StackExchange - Relationship between SVD and PCA. How to use SVD to perform PCA? In Depth: Principal Component Analysis In-Depth: Manifold Learning Recursive Feature Elimination A Tutorial on Principal Component Analysis Principal Component Analysis Explained Step Forward Feature Selection: A Practical Example in Python

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Feature Engineering Feature Scaling with scikit-learn Anthony Goldbloom gives you the secret to winning Kaggle competitions What are some best practices in Feature Engineering? Machine Learning Mastery Fundamental Techniques of Feature Engineering for Machine Learning Feature Engineering Cookbook for Machine Learning Outlier detection with Scikit Learn Working With Text Data WTF is TF-IDF?

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Gentle Introduction to the Bias-Variance Trade-Off in Machine Learning Understanding the Bias-Variance Tradeoff Introduction to Machine Learning Algorithms: Linear Regression 7 Classical Assumptions of Ordinary Least Squares (OLS) Linear Regression Statistics By Jim Tikhonov regularization Ridge Regression for Better Usage Lasso (statistics) Understanding Linear Regression and Regression Error Metrics Understand Regression Performance Metrics

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Confusion matrix and other metrics in machine learning Let’s learn about AUC ROC Curve! Classification Algorithms Comparison Having an Imbalanced Dataset? Here Is How You Can Fix It FOUNDATIONS OF IMBALANCED LEARNING DATA MINING FOR IMBALANCED DATASETS: AN OVERVIEW An Introduction to Logistic Regression: From Basic Concepts to Interpretation with Particular Attention to Nursing Domain Explaining the Success of Nearest Neighbor Methods in Prediction Classification: Basic concepts, decision trees, and model evaluation