000			01974nam a22002057a 4500
999			_c3654 _d3654
005			20221027112838.0
008			221027b ||||| |||| 00| 0 eng d
020			_a9781789616729
082			_a005.133 _bLIU
100			_aLiu, Yuxi _91797
245			_aPython machine learning by example: _bimplement machine learning algorithms and techniques to build intelligent systems
250			_a2nd
260			_bPackt Publishing _aBirmingham _c2019
300			_avi, 355 p.
365			_aUSD _b36.99
520			_aAbout this book The surge in interest in machine learning (ML) is due to the fact that it revolutionizes automation by learning patterns in data and using them to make predictions and decisions. If you’re interested in ML, this book will serve as your entry point to ML. Python Machine Learning By Example begins with an introduction to important ML concepts and implementations using Python libraries. Each chapter of the book walks you through an industry adopted application. You’ll implement ML techniques in areas such as exploratory data analysis, feature engineering, and natural language processing (NLP) in a clear and easy-to-follow way. With the help of this extended and updated edition, you’ll understand how to tackle data-driven problems and implement your solutions with the powerful yet simple Python language and popular Python packages and tools such as TensorFlow, scikit-learn, gensim, and Keras. To aid your understanding of popular ML algorithms, the book covers interesting and easy-to-follow examples such as news topic modeling and classification, spam email detection, stock price forecasting, and more. By the end of the book, you’ll have put together a broad picture of the ML ecosystem and will be well-versed with the best practices of applying ML techniques to make the most out of new opportunities.
650			_aMachine learning _92343
650			_aPython (Computer program language) _99831
942			_2ddc _cBK