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Hands-on machine learning with Sciki...

Géron, Aurélien.

Hands-on machine learning with Scikit-Learn and TensorFlow :concepts, tools, and techniques to build intelligent systems /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	006.31
書名/作者:	Hands-on machine learning with Scikit-Learn and TensorFlow : : concepts, tools, and techniques to build intelligent systems // Aurélien Géron.
作者:	Géron, Aurélien.
出版者:	Sebastopol, CA : : O'Reilly Media,, 2017.
面頁冊數:	xx, 547 p. : : ill. ;; 24 cm.
附註:	Includes index.
標題:	Machine learning.
標題:	Artificial intelligence.
ISBN:	9781491962299 (pbk.) :
內容註:	The fundamentals of machine learning. The machine learning landscape ; End-to-end machine learning project ; Classification ; Training models ; Support vector machines ; Decision trees ; Ensemble learning and random forests ; Dimensionality reduction -- Neural networks and deep learning. Up and running with TensorFlow ; Introduction to artificial neural networks ; Training deep neural nets ; Distributing TensorFlow across devices and servers ; Convolutional neural networks ; Recurrent neural networks ; Autoencoders ; Reinforcement learning -- Exercise solutions -- Machine learning project checklist -- SVM dual problem -- Autodiff -- Other popular ANN architectures.
摘要、提要註:	Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.

Hands-on machine learning with Scikit-Learn and TensorFlow :concepts, tools, and techniques to build intelligent systems /
Géron, Aurélien.

Hands-on machine learning with Scikit-Learn and TensorFlow :concepts, tools, and techniques to build intelligent systems /Aurélien Géron. - 1st ed. - Sebastopol, CA :O'Reilly Media,2017. - xx, 547 p. :ill. ;24 cm.

Includes index.

The fundamentals of machine learning. The machine learning landscape ; End-to-end machine learning project ; Classification ; Training models ; Support vector machines ; Decision trees ; Ensemble learning and random forests ; Dimensionality reduction -- Neural networks and deep learning. Up and running with TensorFlow ; Introduction to artificial neural networks ; Training deep neural nets ; Distributing TensorFlow across devices and servers ; Convolutional neural networks ; Recurrent neural networks ; Autoencoders ; Reinforcement learning -- Exercise solutions -- Machine learning project checklist -- SVM dual problem -- Autodiff -- Other popular ANN architectures.

Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.

ISBN: 9781491962299 (pbk.) :NTD 1,525Subjects--Topical Terms:

202931
Machine learning.

LC Class. No.: Q325.5 / .G47 2017

Dewey Class. No.: 006.31

Hands-on machine learning with Scikit-Learn and TensorFlow :concepts, tools, and techniques to build intelligent systems /
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