Machine learning with Python for everyone

By:

Fenner, Mark E

Material type: Text

TextPublication details: Noida Pearson India Education Services Pvt Ltd 2020Edition: 4th Impression edDescription: xix, 473pISBN:

9789353944902 (pbk.)

Subject(s):

DDC classification:

006.31 FEN

Summary: "The Complete Beginner’s Guide to Understanding and Building Machine Learning Systems with Python Machine Learning with Python for Everyone will help you master the processes, patterns, and strategies you need to build effective learning systems, even if you’re an absolute beginner. If you can write some Python code, this book is for you, no matter how little college-level math you know. Principal instructor Mark E. Fenner relies on plain-English stories, pictures, and Python examples to communicate the ideas of machine learning."

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Book	Plaksha University Library	Computer science	006.31 FEN (Browse shelf(Opens below))	Available		003526
Book	Plaksha University Library	Computer science	006.31 FEN (Browse shelf(Opens below))	Available		003527

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Previous	006.31 DEI Mathematics for machine learning	006.31 DEI Mathematics for machine learning	006.31 FEN Machine learning with Python for everyone	006.31 FEN Machine learning with Python for everyone	006.31 FLA Machine learning : the art and science of algorithms that make sense of data	006.31 FLA Machine learning : the art and science of algorithms that make sense of data	006.31 GIF Practical MLOps : operationalizing machine learning models	Next

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"The Complete Beginner’s Guide to Understanding and Building Machine Learning Systems with Python

Machine Learning with Python for Everyone will help you master the processes, patterns, and strategies you need to build effective learning systems, even if you’re an absolute beginner. If you can write some Python code, this book is for you, no matter how little college-level math you know. Principal instructor Mark E. Fenner relies on plain-English stories, pictures, and Python examples to communicate the ideas of machine learning."

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