Introduction
  • Introduction
  • Additional FREE Content
Getting Started
  • Finding the codes (Github)
  • A Look at the Projects
Intro to Tensors - PyTorch
  • Intro
  • 1 Dimensional Tensors
  • Vector Operations
  • 2 Dimensional Tensors
  • Slicing 3D Tensors
  • Matrix Multiplication
  • Gradient with PyTorch
  • Outro
Linear Regression - PyTorch
  • Intro
  • Making Predictions
  • Linear Class
  • Custom Modules
  • Creating Dataset
  • Loss Function
  • Gradient Descent
  • Mean Squared Error
  • Training - Code Implementation
  • Getting Weird Results?
  • Outro
  • Summary
Perceptrons - PyTorch
  • Intro
  • What is Deep Learning
  • Creating Dataset
  • Perceptron Model
  • Model Setup
  • Model Training
  • Model Testing
  • Outro
Deep Neural Networks - PyTorch
  • Intro
  • Non-Linear Boundaries
  • Architecture
  • Feedforward Process
  • Error Function
  • Backpropagation
  • Code Implementation
  • Testing Model
  • Outro
Image Recognition - PyTorch
  • Intro
  • MNIST Dataset
  • Training and Test Datasets
  • Important Update - Bug fix for next lesson
  • Image Transforms
  • Neural Network Implementation
  • Neural Network Validation
  • Test Links
  • Final Tests
  • A note on adjusting batch size
  • Outro
Convolutional Neural Networks - PyTorch
  • Convolutions and MNIST
  • Convolutional Layer
  • Convolutions II
  • Pooling
  • Fully Connected Network
  • Neural Network Implementation with PyTorch
  • Model Training with PyTorch
CIFAR 10 Classification - PyTorch
  • The CIFAR 10 Dataset
  • Testing LeNet
  • Hyperparameter Tuning
  • Data Augmentation
Transfer Learning - PyTorch
  • Pre-trained Sophisticated Models
  • Github Link for Dataset
  • AlexNet and VGG16
Style Transfer - PyTorch
  • Recommended Paper to Read (Optional)
  • VGG 19
  • Images Required for Next Lesson (Resource)
  • Image Transforms
  • Feature Extraction
  • 2nd Optional Paper to Read
  • The Gram Matrix
  • Optimization
  • Content and Style Images
  • Style Transfer with Video
  • Goodbye, for now
All Source Codes
  • Intro
  • Linear Regression
  • Logistic Regression
  • Deep Neural Networks
  • MNIST Classification
  • Convolutional Neural Networks
  • CIFAR 10
  • Transfer Learning
  • Style Transfer
Appendix A - Python Crash Course (Optional)
  • Python Crash Course - Free Access