Machine Learning with Python for Everyone

By:

Fenner, Mark E

Material type: Text

TextSeries: Addison-Wesley data and analytics seriesPublication details: India: Pearson India, 2020.Edition: 1st EdDescription: i-xxvii+473pISBN:

9789353944902

Subject(s):

Machine learning-- -- Python (Computer program language)

DDC classification:

006.31 FEN.M

Contents:

Predicting categories : getting started with classification -- Predicting numerical values : getting started with regression -- Evaluating and comparing learners -- Evaluating classifiers -- Evaluating regressors -- More classification methods -- More regression methods -- Manual feature engineering : manipulating data for fun and profit -- Turning hyperparameters and pipelines -- Combining learners -- Models that engineer features for us -- Feature engineering for domains : domain-specific learning -- Connection, extensions, and further directions -- mlwpy.py listing.

Summary: ""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. Author 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	Home library	Call number	Status	Date due	Barcode
Book	School of Distance Education, University of Kerala, Kariavattom Campus General Stacks	School of Distance Education, University of Kerala, Kariavattom Campus	006.31 FEN.M (Browse shelf(Opens below))	Available		SDE28920

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Previous	006.3 WIN-A Artificial Intelligence	006.3 WIN-A Artificial Intelligence/	006.31 BHA.M Machine learning for Beginners: Learn to build learning systems using Python	006.31 FEN.M Machine Learning with Python for Everyone	006.31 GOP.A Applied machine learning	006.31 SIL.D Deep learning projects using TensorFlow 2 Neural network development with Python and Keras	006.312 BHU.B Big Data and Hadoop Learn by Example	Next

Predicting categories : getting started with classification --
Predicting numerical values : getting started with regression --
Evaluating and comparing learners --
Evaluating classifiers --
Evaluating regressors --
More classification methods --
More regression methods --
Manual feature engineering : manipulating data for fun and profit --
Turning hyperparameters and pipelines --
Combining learners --
Models that engineer features for us --
Feature engineering for domains : domain-specific learning --
Connection, extensions, and further directions --
mlwpy.py listing.

""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. Author Mark E. Fenner relies on plain-English stories, pictures, and Python examples to communicate the ideas of machine learning."

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