| 000 | 02257nam a22002297a 4500 | ||
|---|---|---|---|
| 999 |
_c56502 _d56502 |
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| 005 | 20200312140053.0 | ||
| 008 | 200312b ||||| |||| 00| 0 eng d | ||
| 020 | _a9789352139057 | ||
| 028 |
_aRaghav Books Private Limited _bA-184 A, Nand Gram, Ghaziabad, U.P. _c1805 _d07/03/2020 |
||
| 082 | _a006.31 GER | ||
| 100 | _aAurélien Géron | ||
| 245 |
_aHands-on machine learning with Scikit-Learn and TensorFlow concepts, tools, and techniques to build intelligent systems _c/Aurélien Géron |
||
| 260 |
_aSebastopol, CA _b: O'Reilly Media _c, 2017 |
||
| 300 |
_axx, 551 pages _c ; 24 cm |
||
| 365 | _b2275 | ||
| 505 | _a Part I. 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 -- Part II. 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 | _aThrough 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. By using concrete examples, minimal theory, and two production-ready Python frameworks--Scikit-Learn and TensorFlow--author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started. | ||
| 650 | _aComputer Science | ||
| 655 |
_aMachine learning _bArtificial intelligence |
||
| 700 | _aAurélien Géron | ||
| 942 | _cBOOK | ||