Neural Networks & Deep Learning Fundamentals¶
Master the fundamentals of neural networks, backpropagation, and how deep learning models learn from first principles Course 03 · Foundations · 10 lessons · ~20h
Lessons¶
| # | Lesson | Duration | Level |
|---|---|---|---|
| 1 | Introduction to Neural Networks & Deep Learning | 25 min | beginner |
| 2 | Neurons, Activation Functions & Forward Propagation | 30 min | beginner |
| 3 | Loss Functions & Measuring Performance | 25 min | beginner |
| 4 | Gradient Descent - The Learning Algorithm | 35 min | intermediate |
| 5 | Backpropagation - How Networks Learn | 40 min | intermediate |
| 6 | Overfitting, Regularization & Dropout | 55 min | intermediate |
| 7 | Building a Neural Network from Scratch | 65 min | intermediate |
| 8 | Convolutional Neural Networks (CNNs) | 55 min | intermediate |
| 9 | Recurrent Neural Networks (RNNs) & LSTMs | 55 min | intermediate |
| 10 | Training Best Practices & Optimization | 60 min | intermediate |
| Start here: Introduction to Neural Networks & Deep Learning | |||
| ## Exercises |
Hands-on files: exercises/index.md