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Introduction to PyTorch Tensors

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Overview

Step into the world of PyTorch, a leading library for deep learning and neural network development. This beginner-oriented course introduces the foundational building blocks of PyTorch, emphasizing tensors and their pivotal role in constructing neural networks. Through practical examples and exercises, you'll develop the skills to start building and experimenting with tensors in PyTorch.

Syllabus

Unit 1: Introduction to PyTorch Tensors

Running Your First PyTorch Tensor Program
Modifying Tensors in PyTorch
Fixing Bugs in Tensor Creation
Creating and Inspecting Tensors
Implementing a PyTorch Tensor

Unit 2: Fundamental Tensor Operations in PyTorch

Running Various Tensor Operations in PyTorch
Switching to Matrix Multiplication in PyTorch
Fixing Matrix Multiplication in PyTorch
Complete the Broadcasted Operations
Mastering PyTorch Tensor Operations

Unit 3: Reshaping and Flattening Tensors in PyTorch

Running Tensor Reshaping and Flattening Code in PyTorch
Reshaping Tensor Dimensions in PyTorch
Fixing Tensor Reshaping Mistake
Flattening Tensors in PyTorch
Mastering Tensor Manipulations in PyTorch

Unit 4: Defining a Dataset with PyTorch Tensors

Batch and Shuffle Data with PyTorch
Adjust Batch Size in DataLoader
Fix Data Loading Code
Batching and Shuffling with DataLoader
Creating Batched TensorDatasets

Unit 5: Processing Tensors with PyTorch Neural Network Layers

Running Neural Network Layers in PyTorch
Adjust Linear Layer Dimensions
Fix Linear Layer Usage
Defining and Applying Activation Functions in PyTorch
Processing Tensors with Neural Networks

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