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

Delve into PyTorch basics: autograd, model classes, datasets, and data loaders. Gain insights into model development while avoiding common pitfalls. Start creating and training your own PyTorch models.

Beginner

92 Lessons

8h

Certificate of Completion

Delve into PyTorch basics: autograd, model classes, datasets, and data loaders. Gain insights into model development while avoiding common pitfalls. Start creating and training your own PyTorch models.

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

184 Playgrounds
20 Quizzes

This course includes

184 Playgrounds
20 Quizzes

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

TAKEAWAY SKILLS

Python

Machine Learning

Deep Learning

Neural Networks

Pytorch

Course Content

1.

Introduction

Get familiar with PyTorch's pythonic nature and foundational concepts designed for beginners.
2.

Visualizing Gradient Descent

Unpack the core of visualizing gradient descent, exploring parameter updates, learning rates, and feature scaling using a linear regression model in Numpy.
3.

A Simple Regression Problem

Master the steps to implement linear regression with PyTorch, covering tensors, autograd, optimizers, and model creation.
4.

Rethinking the Training Loop

Grasp the fundamentals of creating an effective training loop in PyTorch.
5.

Going Classy

Deepen your knowledge of creating and integrating a PyTorch class, enhancing code management.
6.

A Simple Classification Problem

19 Lessons

See how it works to build and evaluate a binary classification model using PyTorch.
7.

Conclusion

1 Lesson

Build on your deep learning skills by exploring further and staying engaged.
8.

Appendix

2 Lessons

Get familiar with setting up Jupyter notebooks and running TensorBoard for deep learning tasks.

Course Author

Trusted by 1.4 million developers working at companies

Anthony Walker

@_webarchitect_

Emma Bostian 🐞

@EmmaBostian

Evan Dunbar

ML Engineer

Carlos Matias La Borde

Software Developer

Souvik Kundu

Front-end Developer

Vinay Krishnaiah

Software Developer

Eric Downs

Musician/Entrepeneur

Kenan Eyvazov

DevOps Engineer

Anthony Walker

@_webarchitect_

Emma Bostian 🐞

@EmmaBostian

Hands-on Learning Powered by AI

See how Educative uses AI to make your learning more immersive than ever before.

Instant Code Feedback

Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

AI-Powered Mock Interviews

Adaptive Learning

Explain with AI

AI Code Mentor