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.