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016	7		_a019326633 _2Uk
020			_a9781492035640 _q(paperback)
020			_a1492035645 _q(paperback)
035			_a(OCoLC)on1066070019
040			_aYDX _beng _cYDX _erda _dBDX _dOCLCQ _dYOM _dUKMGB _dNRC _dSFR _dJRZ _dOCLCF _dOQX _dCLE _dOCLCO _dCUY _dOCL _dNDL _dOCLCA _dOCLCQ _dOCLCO _dDLC
041			_aeng
042			_apcc
050	0	0	_aQA76.73.P98 _bP38 2019
080			_a004.4
100	1		_aPatel, Ankur A., _eauthor.
245	1	0	_aHands-on unsupervised learning using Python : _bhow to build applied machine learning solutions from unlabeled data / _cAnkur A. Patel.
250			_aFirst edition.
264		1	_aSebastopol, CA : _bO'Reilly Media, _c2019.
264		4	_c©2019
300			_axx, 337 pages : _billustrations ; _c24 cm.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references and index.
505	0		_aPart 1. Fundamentals of unsupervised learning. Unsupervised learning in the machine learning ecosystem -- End-to-end machine learning project -- Part 2. Unsupervised learning using Scikit-learn. Dimensionality reduction -- Anomaly detection -- Clustering -- Group segmentation -- Part 3. Unsupervised learning using TensorFlow and Keras. Autoencoders -- Hands-on autoencoder -- Semisupervised learning -- Part 4. Deep unsupervised learning using TensorFlow and Keras. Recommender systems using restricted Boltzmann machines -- Feature detection using deep belief networks -- Generative adversarial networks -- Time series clustering -- Conclusion.
520			_aMany industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to the holy grail in AI research, the so-called general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning cannot be applied; this is where unsupervised learning comes in. Unsupervised learning can be applied to unlabeled datasets to discover meaningful patterns buried deep in the data, patterns that may be near impossible for humans to uncover. Author Ankur Patel provides practical knowledge on how to apply unsupervised learning using two simple, production-ready Python frameworks - scikit-learn and TensorFlow using Keras. With the hands-on examples and code provided, you will identify difficult-to-find patterns in data and gain deeper business insight, detect anomalies, perform automatic feature engineering and selection, and generate synthetic datasets. All you need is programming and some machine learning experience to get started.
650		0	_aPython (Computer program language)
650		0	_aMachine learning.
650		0	_aArtificial intelligence.
650		7	_aArtificial intelligence. _2fast _0(OCoLC)fst00817247
650		7	_aMachine learning. _2fast _0(OCoLC)fst01004795
650		7	_aPython (Computer program language) _2fast _0(OCoLC)fst01084736
655		7	_aHandbooks and manuals. _2fast _0(OCoLC)fst01423877
655		7	_aHandbooks and manuals. _2lcgft
906			_a7 _bcbc _cpccadap _d2 _encip _f20 _gy-gencatlg
909			_c3
942			_2udc _cEE _n0
999			_c1540 _d1540