Book Content
chapters • 14h24m total length
1. Introduction to Machine Learning
2. Setup and Introduction to Deep Learning Frameworks
3. Preparing Data
4. Learning from Data
5. Training a Single Neuron
6. Training Multiple Layers of Neurons
7. Autoencoders
8. Deep Autoencoders
9. Variational Autoencoders
10. Restricted Boltzmann Machines
11. Deep and Wide Neural Networks
12. Convolutional Neural Networks
13. Recurrent Neural Networks
14. Generative Adversarial Networks
15. Final Remarks on The Future of Deep Learning
