Book Content
chapters • 16h8m total length
1. Getting Started with Deep Learning
2. A First Look at TensorFlow
3. Feed-Forward Neural Networks with TensorFlow
4. Convolutional Neural Networks
5. Optimizing TensorFlow Autoencoders
6. Recurrent Neural Networks
7. Heterogeneous and Distributed Computing
8. Advanced TensorFlow Programming
9. Recommendation Systems using Factorization Machines
10. Reinforcement Learning
