Book Content
chapters • 15h total length
1. Overview of Deep Learning Using PyTorch
2. Combining CNNs and LSTMs
3. Deep CNN Architectures
4. Deep Recurrent Model Architectures
5. Hybrid Advanced Models
6. Music and Text Generation with PyTorch
7. Neural Style Transfer
8. Deep Convolutional GANs
9. Deep Reinforcement Learning
10. Operationalizing Pytorch Models into Production
11. Distributed Training
12. PyTorch and AutoML
13. PyTorch and Explainable AI
14. Rapid Prototyping with PyTorch
