This is the repository which houses all the code for the Kickstart AI course on Udemy. From Tensorflow Live Lessons by Jon Krohn
The course consists of 3 sections:
Lectures:
- Getting Started
- Introduction
- Technology behind neural networks
- Types of Layers
- Code Walkthrough (Dense Neural Networks for MNIST Digit Classification)
- AI Testing and Optimization
- Code Walkthrough (AI Testing and Optimization)
Assignment: Fashion MNIST, Dogs Vs. Cats, Oxford Flowers
Lectures:
- Overview of NLP and its Relatives
- Preprocessing steps for NLP
- Modeling Natural Language Data
- Recurrent Neural Networks
- Long Short Term Memory Networks
- Understanding the Difference between RNNs and LSTMs
- Code Walkthrough (LSTM for IMDB Sentiment Classification)
- New types of Neural Network Architectures
Assignment: Reuters Newswire topics classification
Lectures:
- Applications of GANs and Reinforcement Learning
- Theory of GANs and the Quick, Draw! Dataset
- Code Walkthrough (GANs to draw an image of an apple)
- Deep Reinforcement Learning
- Code Walkthrough 2 (DQN for Cartpole Game)
Assignment: Generate Different Images using with the Quick, Draw! dataset, Create a Reinforcement Learning agent for the game Pong
- Bonus Lecture: Boltzmann Machines
- Summary of the Course