Book Content
chapters • 18h56m total length
1. Building a neural network with Tensorflow and Keras
2. Building a deep neural network
3. Applications of deep feed forward neural networks
4. Building a deep convolutional neural networ
5. Transfer Learning
6. Object detection and localization
7. Applications of image analysis in self-driving car
8. Image generation
9. Encoding inputs
10. Text analysis using word vectors
11. Building a Recurrent neural Network
12. Applications of many to one architecture based RNN
13. Sequence to Sequence learning
14. End to end learning
15. Audio analysis
16. Reinforcement learning
