Szczegóły ebooka

Deep Learning with Keras. Implementing deep learning models and neural networks with the power of Python

Deep Learning with Keras. Implementing deep learning models and neural networks with the power of Python

Antonio Gulli, Sujit Pal

Ebook
This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and more sophisticated deep convolutional networks. You will also explore image processing with recognition of handwritten digit images, classification of images into different categories, and advanced objects recognition with related image annotations. An example of identification of salient points for face detection is also provided.

Next you will be introduced to Recurrent Networks, which are optimized for processing sequence data such as text, audio or time series. Following that, you will learn about unsupervised learning algorithms such as Autoencoders and the very popular Generative Adversarial Networks (GANs). You will also explore non-traditional uses of neural networks as Style Transfer.

Finally, you will look at reinforcement learning and its application to AI game playing, another popular direction of research and application of neural networks.
  • 1. Neural Networks Foundations
  • 2. Keras Installation and API
  • 3. Deep Learning with ConvNets
  • 4. Generative Adverserial Networks and Wavenet
  • 5. Word Embeddings
  • 6. Recurrent Neural Network — RNN
  • 7. Additional Deep Learning models
  • 8. AI Game Playing
  • 9. Conclusion
  • Tytuł: Deep Learning with Keras. Implementing deep learning models and neural networks with the power of Python
  • Autor: Antonio Gulli, Sujit Pal
  • Tytuł oryginału: Deep Learning with Keras. Implementing deep learning models and neural networks with the power of Python
  • ISBN: 9781787129030, 9781787129030
  • Data wydania: 2017-04-26
  • Format: Ebook
  • Identyfikator pozycji: e_15id
  • Wydawca: Packt Publishing