Machine Learning (ML) Projects and Tutorials

Machine learning experiments and analysis using Jupyter notebooks.

Description

This repository contains a collection of machine learning projects and tutorials, covering topics like regression, classification, clustering, and deep learning. Each project includes code examples and explanations to help you understand key ML concepts.

Project Structure

machine-learning-py/
├── source/         # ML code (.ipynb files)
├── data/           # Datasets
├── .gitignore
└── README.md

Setup

1. Create conda environment:

conda create -n ml-env python=3.10
conda activate ml-env

2. Install packages as needed:

conda install jupyter pandas numpy scikit-learn matplotlib seaborn

3. Start Jupyter:

jupyter notebook

Workflow

• Add notebooks to source/ folder
• Store data in data/