Deep Learning with PyTorch Step-by-Step: Part I - Fundamentals

INTERACTIVE COURSE

Deep Learning with PyTorch Step-by-Step: Part I - Fundamentals

Beginner

92 Lessons

8h

Certificate of Completion

Deep Learning with PyTorch Step-by-Step: Part I - Fundamentals

184 Playgrounds

20 Quizzes

169 Illustrations

Course Overview

This course is designed to provide you with an easy-to-follow, structured, incremental, and from-first-principles approach to learning PyTorch. In this course, you’ll be introduced to the fundamentals of PyTorch: autograd, model classes, datasets, data loaders, and more. You will develop, step-by-step, not only the models themselves but also your understanding of them. You'll be shown both the reasoning behind the code and how to avoid some common pitfalls and errors along the way. By the time you finish th...Show More

Course Content

1

Introduction

Course Overview

2

Visualizing Gradient Descent

Gradient Descent

Data Generation Basic Steps for Using Gradient Descent (Step 0 and 1)Step 2a - Compute the Loss Step 2b - Computing the Loss Surface Step 3 - Compute the Gradients Step 4 - Update the Parameters Learning Rate Scaling the Dataset Step 5 - Rinse and Repeat!Recap Quiz Challenge 1 - Visualizing Gradient Descent Solution Review - Visualizing Gradient Descent

3

A Simple Regression Problem

4

Rethinking the Training Loop

Spoilers Introducing Higher-Order Functions Rethinking the Training Loop Building a Dataset DataLoader Quiz Mini-Batch Inner Loop and Training Split Evaluation TensorBoard SummaryWriter Saving and Loading Models Deploying / Making Predictions Putting It All Together Recap Quiz Challenge 3 - Rethinking the Training Loop Solution Review - Rethinking the Training Loop

5

Going Classy

Spoilers Going Classy Functions

Different Method Types Training Methods Saving and Loading Methods Finalising the Methods needed for going Classy Classy Pipeline Model Training and Predictions Checkpointing Putting It All Together Recap Quiz Challenge 4 - Going Classy Solution Review - Going Classy

6

A Simple Classification Problem

19 Lessons

7

Conclusion

1 Lesson

8

Appendix

2 Lessons

COURSE AUTHOR

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