机读格式显示(MARC)
- 000 02211cam a2200361 i 4500
- 008 171101r20172017cc a b 001 0 eng d
- 020 __ |a 9787564173715 |q paperback
- 040 __ |a SCNU |b eng |c SCNU |e rda |d XJT
- 050 _4 |a Q325.5 |b .G47 2017
- 099 __ |a CAL 022017115006
- 100 1_ |a Géron, Aurélien, |e author.
- 245 10 |a Hands-on machine learning with Scikit-Learn & TensorFlow = |b Scikit-Learn与TensorFlow机器学习实用指南 / |c Aurélien Géron著.
- 246 3_ |a Hands-on machine learning with Scikit-Learn and TensorFlow
- 246 31 |a Scikit-Learn与TensorFlow机器学习实用指南
- 264 _1 |a 南京 : |b 东南大学出版社, |c 2017.
- 300 __ |a xx, 543 pages : |b illustrations ; |c 24 cm
- 336 __ |a text |2 rdacontent
- 337 __ |a unmediated |2 rdamedia
- 338 __ |a volume |2 rdacarrier
- 504 __ |a Includes bibliographical references and index.
- 505 0_ |a 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.
- 520 __ |a 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.
- 534 __ |p Reprint. Originally published: |c Sebastopol, CA : O'Reilly Media, 2017. |z 9781491962299 (pbk.)
- 650 _0 |a Machine learning.
- 650 _0 |a Artificial intelligence.
- 950 __ |a JHUL |b TP181 |c G999