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Machine Learning with TensorFlow

紀錄類型:	書目-語言資料,印刷品 : 單行本
作者:	MattmannChris A.,
其他作者:	PenberthyScott.,
出版地:	Shelter Island, NY
出版者:	Manning Publications Co.;
出版年:	c2020.
版本:	2nd ed.
面頁冊數:	xxix, 420 p.ill. : 24 cm.;
標題:	Machine learning. -
標題:	Data mining. -
標題:	Computer algorithms. -
標題:	Programming languages (Electronic computers) -
標題:	Computer algorithms. -
標題:	Data mining. -
標題:	Machine learning. -
標題:	Programming languages (Electronic computers) -
附註:	Includes index.
摘要註:	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.--Source other than the Library of Congress.
ISBN:	9781617297717
內容註:	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.

Machine Learning with TensorFlow
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215 1 $a xxix, 420 p. $c ill. $d 24 cm.
300 $a Includes index.
327 1 $a Part 1. Your machine-learning rig. 1. A machine-learning odyssey $a 2. TensorFlow essentials $a Part 2. Core learning algorithms. 3. Linear regression and beyond $a 4. Using regression for call-center volume prediction $a 5. A gentle introduction to classification $a 6. Sentiment classification : large movie-review dataset $a 7. Automatically clustering data $a 8. Inferring user activity from Android accelerometer data $a 9. Hidden Markov models $a 10. Part-of-speech tagging and word-sense disambiguation $a Part 3. The neural network paradigm. 11. A peek into autoencoders $a 12. Applying autoencoders: the CIFAR-10 image dataset $a 13. Reinforcement learning $a 14. Convolutional neural networks $a 15. Building a real-world CNN: VGG-Face and VGG-Face Lite $a 16. Recurrent neural networks $a 17. LSTMs and automatic speech recognition $a 18. Sequence=to-sequence models for chatbots $a 19. Utility landscape.
330 $a 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.--Source other than the Library of Congress.
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