Book Content
chapters • 9h4m total length
1. Setup and introduction to TensorFlow
2. Deep Learning and Convolutional Neural Networks
3. Image Classification in Tensorflow
4. Object Detection and Segmentation
5. VGG, Inception Modules, Residuals, and MobileNets
6. Autoencoders, Variational Autoencoders, and Generative Adversarial Networks
7. Transfer Learning
8. Machine Learning Best Practices and Troubleshooting
9. Training at Scale
