The grand finale. Machine learning is where Python really shines. This section won't make you an ML expert overnight, but it will give you a solid foundation to understand what ML is, how it works, and how to build your first models.
Note: This section requires installing third-party packages. Each lesson includes setup instructions.
| # | Lesson | Description |
|---|---|---|
| 01 | ML Concepts | What is ML? Types of learning, key terminology |
| 02 | scikit-learn Basics | Your first ML models — classification and regression |
| 03 | Simple Neural Network | Building a neural network from scratch and with PyTorch |
pip install scikit-learn torch numpy pandas matplotlib- Understand the difference between supervised and unsupervised learning
- Train classification and regression models with scikit-learn
- Evaluate model performance with proper metrics
- Build a simple neural network
- Section 09: Data Processing — NumPy and Pandas are essential
- A basic understanding of math (mean, standard deviation, basic algebra)