Book Content
chapters • 11h56m total length
1. What is Machine Learning?
2. Neural Networks and Deep Learning
3. TensorFlow Graph Architecture
4. TensorFlow 2.0 Architecture
5. Efficient Data Input Pipelines and Estimator API
6. Image Classification using TensorFlow Hub
7. Introduction to Object Detection
8. Semantic Segmentation and Custom Dataset Builder
9. Generative Adversarial Networks
10. Bringing a Model to Production














