000			01574nam a22001935i 4500
999			_c44553 _d44553
020			_a9781484234495 (hard : alk. paper)
082			_a005.133 _bMUK
100			_aMukhopadhyay, Sayan
245	0	0	_aAdvanced data analytics using Python /
260			_a[New York?] : _b Apress, _c©2018
300			_a186 pages :
500			_aIncludes index.
505			_a Introduction -- ETL with Python (structured data) -- Supervised learning using Python -- Unsupervised learning : clustering -- Deep learning and neural networks -- Time series -- Analytics at scale.
520			_a"Gain a broad foundation of advanced data analytics concepts and discover the recent revolution in databases such as Neo4j, Elasticsearch, and MongoDB. This book discusses how to implement ETL techniques including topical crawling, which is applied in domains such as high-frequency algorithmic trading and goal-oriented dialog systems. You'll also see practical examples of machine learning concepts such as semi-supervised learning, deep learning, computer vision and NLP. Practical Data Analytics with Python also covers important traditional data analysis techniques such as time series, principal component analysis through examples from real industry projects. After reading this book you will have experience of every technical aspect of an industrial analytics project. You'll get to know the concepts using Python code, thoroughly explained in each case."--
650			_aPython (Computer program language)
650			_aMachine learning.
650			_aData mining.
942			_cREF