Title Statements
- Full title :Machine learning with TensorFlow / Chris Mattmann ; foreword by Scott Penberthy.
Summary
"Updated with new code, new projects, and new chapters, Machine Learning with TensorFlow, Second Edition, gives readers a solid foundation in machine-learning concepts and the TensorFlow library. Summary Updated with new code, new projects, and new chapters, Machine Learning with TensorFlow, Second Edition gives readers a solid foundation in machine-learning concepts and the TensorFlow library."--
Read More ↓Edition Statements
- Publication Date:2020
- Edition:Second edition
Publication Statements
- Publisher(s):Manning
- Place of Publication:Shelter Island, NY
- Language:eng
- Publication Date:2020
The Physical Object
- Description:xxix, 420 pages : : illustrations, graphiques ; : 24 cm.
Edition Identifiers
- ISBN:9781617297717, 1617297712
- oclc:on1256818661
- LC Classification:Q325.5
Table of Contents
Part 1. Your machine-learning rig. 1. A machine-learning odyssey -- 2. TensorFlow essentials -- Part 2. Core learning algorithms. 3. Linear regression and beyond -- 4. Using regression for call-center volume prediction -- 5. A gentle introduction to classification -- 6. Sentiment classification : large movie-review dataset -- 7. Automatically clustering data -- 8. Inferring user activity from Android accelerometer data -- 9. Hidden Markov models -- 10. Part-of-speech tagging and word-sense disambiguation -- Part 3. The neural network paradigm. 11. A peek into autoencoders -- 12. Applying autoencoders: the CIFAR-10 image dataset -- 13. Reinforcement learning -- 14. Convolutional neural networks -- 15. Building a real-world CNN: VGG-Face and VGG-Face Lite -- 16. Recurrent neural networks -- 17. LSTMs and automatic speech recognition -- 18. Sequence-to-sequence models for chatbots -- 19. Utility landscape.
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