Machine learning using python / Manaranjan Pradhan, U. Dinesh Kumar.

By:

Pradhan,M & Kumar,D

Material type: Text

TextPublication details: New Delhi : Wiley India Pvt.Ltd., 2019.Description: xx, 343 p. : ill. ; 24 cmISBN:

9788126579907

Subject(s):

Machine learning Python (Computer program language)

DDC classification:

005.133 PRA

Summary: This book is written to provide a strong foundation in machine learning using Python libraries by providing real-life case studies and examples. It covers topics such as foundations of machine learning, introduction to Python, descriptive analytics and predictive analytics. Advanced machine learning concepts such as decision tree learning, random forest, boosting, recommended systems, and text analytics are covered. The book takes a balanced approach between theoretical understanding and practical applications. All the topics include real-world examples and provide step-by-step approach on how to explore, build, evaluate, and optimize machine learning models.

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Holdings
Item type	Current library	Collection	Call number	Status	Notes	Date due	Barcode
Donated Books	Symbiosis Institute of Business Management-(SIBM-Nagpur)		005.133 PRA (Browse shelf(Opens below))	Available			SIUNG-DB-30
Books	Symbiosis Institute of Geoinformatics	Text Book	005.133/PRA/KUM (Browse shelf(Opens below))	Available	Machine Learning, Python		SIG-B-1041

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This book is written to provide a strong foundation in machine learning using Python libraries by providing real-life case studies and examples. It covers topics such as foundations of machine learning, introduction to Python, descriptive analytics and predictive analytics. Advanced machine learning concepts such as decision tree learning, random forest, boosting, recommended systems, and text analytics are covered. The book takes a balanced approach between theoretical understanding and practical applications. All the topics include real-world examples and provide step-by-step approach on how to explore, build, evaluate, and optimize machine learning models.

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