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The data science handbook

Record Type:	Language materials, printed : Monograph/item
Title/Author:	The data science handbook/ Field Cady.
Author:	Cady, Field,
Published:	Hoboken, NJ :John Wiley & Sons, : c2025.,
Description:	1 online resource (xix, 347 p.) :ill. (some col.) :
Subject:	Databases - Congresses. -
Online resource:	https://onlinelibrary.wiley.com/doi/book/10.1002/9781394234523
ISBN:	9781394234523

The data science handbook
Cady, Field,1984-

The data science handbook[electronic resource] /Field Cady. - 2nd ed. - Hoboken, NJ :John Wiley & Sons,c2025. - 1 online resource (xix, 347 p.) :ill. (some col.)

Includes bibliographical references and index.

Introduction -- The Data Science Road Map -- Programming Languages -- Data Munging: String Manipulation, Regular Expressions, and Data Cleaning -- Visualizations and Simple Metrics -- AI and Machine Learning Overview -- Interlude: Feature Extraction Ideas -- Machine Learning Classification -- Technical Communication and Documentation -- Unsupervised Learning: Clustering and Dimensionality Reduction -- Regression -- Data Encodings and File Formats -- Big Data -- Databases -- Software Engineering Best Practices -- Traditional Natural Language Processing -- Time Series Analysis -- Probability -- Statistics -- Programming Language Concepts -- Performance and Computer Memory -- Computer Memory and Data Structures -- Maximum Likelihood Estimation and Optimization -- Deep Learning and AI -- Stochastic Modeling -- Parting Words: Your Future as a Data Scientist.

"The goal of this book is to turn you into a data scientist, and there are two parts to this mission. Firstly there is a set of specific concepts, tools and techniques that you can go out and solve problems with today. They include buzzwords such machine learning, Spark and NLP. They also include concepts that are distinctly less sexy but often more useful, like regular expressions, unit tests and SQL queries. It would be impossible to give an exhaustive list in any single book, but I cast a wide net"--

ISBN: 9781394234523Subjects--Topical Terms:

675256
Databases
--Congresses.

LC Class. No.: QA76.9.D32 / C33 2025

Dewey Class. No.: 005.74

The data science handbook
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050 4 $a QA76.9.D32 $b C33 2025
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100 1 $a Cady, Field, $d 1984- $3 1498014
245 1 4 $a The data science handbook $h [electronic resource] / $c Field Cady.
250 $a 2nd ed.
260 $a Hoboken, NJ : $b John Wiley & Sons, $c c2025.
300 $a 1 online resource (xix, 347 p.) : $b ill. (some col.)
504 $a Includes bibliographical references and index.
505 0 $a Introduction -- The Data Science Road Map -- Programming Languages -- Data Munging: String Manipulation, Regular Expressions, and Data Cleaning -- Visualizations and Simple Metrics -- AI and Machine Learning Overview -- Interlude: Feature Extraction Ideas -- Machine Learning Classification -- Technical Communication and Documentation -- Unsupervised Learning: Clustering and Dimensionality Reduction -- Regression -- Data Encodings and File Formats -- Big Data -- Databases -- Software Engineering Best Practices -- Traditional Natural Language Processing -- Time Series Analysis -- Probability -- Statistics -- Programming Language Concepts -- Performance and Computer Memory -- Computer Memory and Data Structures -- Maximum Likelihood Estimation and Optimization -- Deep Learning and AI -- Stochastic Modeling -- Parting Words: Your Future as a Data Scientist.
520 $a "The goal of this book is to turn you into a data scientist, and there are two parts to this mission. Firstly there is a set of specific concepts, tools and techniques that you can go out and solve problems with today. They include buzzwords such machine learning, Spark and NLP. They also include concepts that are distinctly less sexy but often more useful, like regular expressions, unit tests and SQL queries. It would be impossible to give an exhaustive list in any single book, but I cast a wide net"-- $c Provided by publisher.
588 $a Description based on online resource; title from digital title page (viewed on November 13, 2024)
650 0 $a Databases $v Congresses. $3 675256 $3 735810
650 0 $a Statistics $x Data processing $3 1001836
650 0 $a Big data $v Congresses. $3 882536
650 0 $a Information theory $v Congresses. $3 665444 $3 727788
856 4 0 $u https://onlinelibrary.wiley.com/doi/book/10.1002/9781394234523