Skip to content
View Ehsan-999's full-sized avatar

Block or report Ehsan-999

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
Ehsan-999/README.md

Header Image

Hi 👋, I'm Ehsan

🚀 A Passionate Developer

Typing SVG


  • 🌱 I’m currently learning Python
  • ⚡ Fun fact: There are more than 700 coding languages!

🌐 Connect with Me

LinkedIn Gmail


🛠️ Languages & Tools

C# SQL Server Python numpy pandas qt scitlearn Flask fastapi JavaScript HTML5 CSS3


📊 GitHub Stats

GitHub Stats

GitHub Streak

Top Languages


🧠 Fun Projects Soon...

Stay tuned for some cool open-source tools & side projects I'm working on! 🔧


Pinned Loading

  1. Inventory-Management-System-Cs-WinForms-and-SQL-Server Inventory-Management-System-Cs-WinForms-and-SQL-Server Public

    A C# WinForms + SQL Server inventory system with user login, product registration, stock tracking, and transaction logging. Shows real-time stock based on product entries/exits. Includes category f…

    C# 3

  2. Customer-Segmentation-with-Clustering-Algorithms Customer-Segmentation-with-Clustering-Algorithms Public

    This project applies multiple unsupervised learning techniques to segment customers based on their demographic and spending behavior.

    Jupyter Notebook 1

  3. Heart-Disease-Prediction-with-Logistic-Regression Heart-Disease-Prediction-with-Logistic-Regression Public

    This project uses Logistic Regression to predict the presence of heart disease based on medical features such as age, blood pressure, cholesterol, heart rate, and ECG results.

    Jupyter Notebook 1

  4. Housing-price-prediction Housing-price-prediction Public

    This project uses Linear Regression in Python to predict house prices based on features such as area, number of rooms, parking, warehouse, elevator, and location (address).

    Jupyter Notebook