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