This repo contains the presentations and the colab notebooks used in the 3-week 9-session webinar on Machine Learning and Neural Networks

In this 3-week, 9-part, hands-on webinar, participants will gain a strong understanding of the basic principles of machine learning and neural networks. Each session, outlined below, will offer practical applications of machine learning models to image-based applications. Instructor Rajesh Sharma, of Walt Disney Animation Studios, will help participants build intuition around a topic and reinforce that with related mathematics. You’ll walk away with the ability to apply those foundations to engineering solutions using available tools.

YouTube Playlist

• Intro to Machine Learning, Neural Networks, Google Colab, and Data Processing (8 June)
• Regression, Feed-forward Neural Networks, and Classification (10 June)
• Image Data and TensorFlow, Autoencoders (12 June)
• Denoising Autoencoders and Convolutional Neural Networks, or CNN (15 June)
• Transfer Learning and Facial Recognition (17 June)
• Variational Autoencoders (19 June)
• Generative Adversarial Networks, or GAN (22 June)
• Recurrent Neural Networks, or RNN (24 June)
• Reinforcement Learning (26 June)

Pre-requisites:

• Basic Python programming knowledge
• High-school level linear algebra
• High-school level probability and statistics