Intro-to-Deep-Learning

with Google TensorFlow

Course Materials Created and Curated by Karen Mazidi

Course Outline:

Part 1: Foundations

• Python Fundamentals
• Linear Models and ML Basics
• Neural Network and Deep Learning Foundations

Part 2: Deep Learning with TF Keras

• Sequential Models; Keras API and Functional API
• TF Possibilities
• CNNs
• RNNs, LSTMs, GRUs
• Sequence-to-Sequence Models
• More about Embeddings

Part 3: Advanced Techniques

• Custom loss functions, layers, models, and callbacks
• Transfer Learning
• Autoencoders and stacked autoencoders
• GANs
• SNNs

For best results, download the notebooks, copy to your Google drive, and run in Google colab.

With much appreciation to Google for the grant and other course support.