PyTorch Essential Training: Deep Learning
Offered By: LinkedIn Learning
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
- Introduction to deep learning
- Why should you use PyTorch
- Google Colaboratory basics
- Introduction to tensors
- Creating a tensor CPU example
- Creating a tensor GPU example
- Moving tensors between CPUs and GPUs
- Different ways to create tensors
- Tensor attributes
- Tensor data types
- Creating tensors from random samples
- Creating tensors like other tensors
- Solution: Create tensors
- Tensor operations
- Mathematical functions
- Linear algebra operations
- Automatic differentiation (Autograd)
- Solution: Split tensors to form new tensors
- Introduction to the DL training process
- Data preparation
- Data loading
- Data transforms
- Data batching
- Model development and training
- Validation and testing
- Next steps
Taught by
Jonathan Fernandes
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