PyTorch Essential Training: Deep Learning

Offered By: LinkedIn Learning

Tags

PyTorch Courses Deep Learning Courses Neural Networks Courses Linear Algebra Courses Data Preparation Courses GPU Computing Courses Tensors Courses Model Training Courses Autograd Courses

Course Description

Overview

Explore the basics of deep learning using PyTorch and test your knowledge with hands-on challenges.

Syllabus

Introduction

Deep learning with PyTorch
What you should know
Tour of CoderPad

1. PyTorch Overview and Introduction to Google Colaboratory

Introduction to deep learning
Why should you use PyTorch
Google Colaboratory basics

2. Tensors

Introduction to tensors
Creating a tensor CPU example
Creating a tensor GPU example
Moving tensors between CPUs and GPUs

3. Creating Tensors

Different ways to create tensors
Tensor attributes
Tensor data types
Creating tensors from random samples
Creating tensors like other tensors
Solution: Create tensors

4. Manipulate Tensors

Tensor operations
Mathematical functions
Linear algebra operations
Automatic differentiation (Autograd)
Solution: Split tensors to form new tensors

5. Developing a Deep Learning Model

Introduction to the DL training process
Data preparation
Data loading
Data transforms
Data batching
Model development and training
Validation and testing

Conclusion

Next steps

Taught by

Jonathan Fernandes

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