Table of Content
 


Module 1

GETTING STARTED WITH PYTORCH

  • The Course Overview
  • Introduction to PyTorch
  • Installing PyTorch on Linux and Windows
  • Installing CUDA
  • Introduction to Tensors and Variables
  • Working with PyTorch and NumPy
  • Working with PyTorch and GPU
  • Handling Datasets in PyTorch
  • Deep Learning Using PyTorch

TRAINING YOUR FIRST NEURAL NETWORK

  • Building a Simple Neural Network
  • Loss Functions in PyTorch
  • Optimizers in PyTorch
  • Training the Neural Network
  • Saving and Loading a Trained Neural Network
  • Training the Neural Network on a GPU

COMPUTER VISION – CNN FOR DIGITS RECOGNITION

  • Computer Vision Motivation
  • Convolutional Neural Networks
  • The Convolution Operation
  • Concepts - Strides, Padding, and Pooling
  • Loading and Using MNIST Dataset
  • Building the Model
  • Training and Testing

SEQUENCE MODELS – RNN FOR TEXT GENERATION

  • Sequence Models Motivation
  • Word Embedding
  • Recurrent Neural Networks
  • Building a Text Generation Model in PyTorch
  • Training and Testing

AUTOENCODER - DENOISING IMAGES

  • Autoencoders Motivation
  • How Autoencoders Work
  • Types of Autoencoders
  • Building Denoising Autoencoder Using PyTorch
  • Training and Testing

REINFORCEMENT LEARNING – BALANCE CARTPOLE USING DQN

  • Reinforcement Learning Motivation
  • Reinforcement Learning Concepts
  • DQN, Experience Replay
  • The OpenAI Gym Environment
  • Building the Cartpole Agent Using DQN
  • Training and Testing

Module 2

FIRST STOP: A QUICK INTRODUCTION TO PYTORCH

  • The Course Overview
  • What Makes PyTorch Special?
  • Installing PyTorch

SLEEPING UNDER THE STARS: IT'S A BIRD...IT'S A PLANE...IT’S A CNN?

  • Problem: Detect a Specific Type of Object in an Image
  • Quick Win: Using a Pretrained AlexNet Model for Beaver Detection
  • Getting and Preparing Image Data
  • Building, Training, and Testing Your Model
  • Using Your Model to Detect Beavers and What’s Next?

GOING ABROAD: LANGUAGE DETECTION FOR FUN AND PROFIT WITH RNN

  • Problem: Recognize the Language of a Specific Text
  • Understanding and Preparing Language Data
  • Building, Training, and Testing Your Model for Language Detection
  • Using Your Model to Detect Languages and What’s Next?

MAKING FRIENDS: LOST IN TRANSLATION WITH LSTM

  • Problem: Translate a Specific Text from One Language to Another
  • Understanding and Preparing Dataset for Language Translation
  • Building, Training, and Testing Your Models for Language Translation
  • Using Your Models for Language Translation

GETTING SOME CULTURE: BECOMING A DEEP NEURAL PICASSO WITH DNN

  • Problem: Extract Key Style Features from One Image and Use It on Another One
  • Preparing Images for Style Transfer
  • Building and Training Style Transfer Model


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