MACHINE LEARNING WITH PYTHON COOKBOOK

By:

ALBON, CHRIS

Material type: Text

TextPublication details: Navi Mumbai Shroff Publishers and Distributors Pvt. Ltd 2019Description: xiii, 349pISBN:

9789352137305

Subject(s):

MACHINE LEARNING, PYTHON (COMPUTER PROGRAM LANGUAGE)

DDC classification:

006.31/ALB

Summary: About this book practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics. Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help construct your application. Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications.

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Holdings
Item type	Current library	Call number	Status	Notes	Date due	Barcode
Books	Symbiosis Institute of Computer Studies and Research Programming Language	006.31/ALB (Browse shelf(Opens below))	Available	MACHINE LEARNING, PYTHON (COMPUTER PROGRAM LANGUAGE)		SICSR-B-19629

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About this book practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics.
Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help construct your application. Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications.

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