Notebooks and Supporting files for Tensorflow 2.0 Tutorials
This repository contains notebooks that provide introductory and advanced lessons on tensorflow 2.0. It also contains slides (as png images) that are used in the notebooks.
The introductory notebooks cover:
- introduction to deep learning and tensorflow 2.0
- introduction to computer vision
- introduction to transfer learning
The advanced notebooks will cover:
- tensors and dimensions in deep learning
- custom models and layers
- custom training loops
- data augmentation and pipelines
And are based on research on the Tensorflow 2.0 website, Francois Chollet's Deep Learning with Python notebook, and the Aurelian Guerion book (second edition).
The notebooks were used in:
- Data Science for the Internet of Things MeetUp on 29 June 2019.
They will be used as part of the 'Artificial Intelligence: Cloud and Edge Implementations' University of Oxford Course.