Deep Learning Fundamentals: Code Materials and Exercises

This repository contains code materials & exercises for Deep Learning Fundamentals course by Sebastian Raschka and Lightning AI.

• Link to the course website:
• Link to the discussion forum: https://github.com/Lightning-AI/dl-fundamentals/discussions
• Reach out to Lightning & Sebastian on social media: @LightningAI @rasbt

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For other announcements, updates, and additional materials, you can follow Lightning AI and Sebastian on Twitter!

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Links to the materials

Unit 1. Welcome to Machine Learning and Deep Learning

• 1.6 Implementing a Perceptron in Python
• Unit 1 exercises
  • Exercise 1: Add early-stopping to make the Perceptron more efficient
  • Exercise 2: Initialize the model parameters with small random numbers instead of 0's
  • Exercise 3: Use a learning rate for updating the weights and bias unit

Unit 2. First Steps with PyTorch: Using Tensors

• 2.2 What Are Tensors?
• 2.3 How Do We Use Tensors in PyTorch?
• 2.4 Improving Code Efficiency with Linear Algebra
• 2.5 Debugging Code
• 2.6 Revisiting the Perceptron Algorithm
• Unit 2 exercises
  • Exercise 1: Introducing more PyTorch functions to make your code more efficient
  • Exercise 2: Make the perceptron more efficient using matrix multiplication

Unit 3. Coming Soon

Unit 4. Coming Soon

Unit 5. Coming Soon

Unit 6. Coming Soon

Unit 7. Coming Soon

Unit 8. Coming Soon

Unit 9. Coming Soon

Unit 10. Coming Soon