Book Content
chapters • 11h44m total length
1. Revisiting Deep Learning architecture and techniques
2. Deep Neural Networks for multiclass classification
3. Deep Neural Networks for regression
4. Image classification and recognition
5. Image classification using convolutional neural networks
6. Applying Autoencoder neural networks using Keras
7. Image classification for small data using transfer learning
8. Creating new images using generative adversarial networks
9. Deep network for text classification
10. Text classification using recurrent neural networks
11. Text classification using Long Short-Term Memory Network
12. Text classification using convolutional recurrent networks
13. Tips, tricks and the road ahead
