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Frontiers in Data Science

Frontiers in Data Science deals with philosophical and practical results in Data Science. A broad definition of Data Science describes the;

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Frontiers in Data Science

Frontiers in Data Science deals with philosophical and practical results in Data Science. A broad definition of Data Science describes the;

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Practical Data Science

lakes into business assets. The data science technology stack demonstrated in Practical Data Science is built from components in general use;

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Practical Data Science with Hadoop and Spark

professionals who can solve real data science problems with Hadoop and Spark. Practical Data Science with Hadoop (R) and Spark is your complete guide to;

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Introduction to Data Science

parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis;

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Principles of Strategic Data Science

theory of data science Augment your coding knowledge with practical data science techniques for efficient data analysis Learn practical ways to;

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Big Data and Social Science

Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides;

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Practical Data Science with Python 3

for data science and how to document data engineering practices. This book is a good starting point for people who want to gain practical;

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Practical Data Science with Python 3

software for data science and how to document data engineering practices. This book is a good starting point for people who want to gain practical;

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Doing Data Science in R

Explores the foundations of data science and breaks down the processes involved, focusing on the link between data science and practical social;

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Principles of Data Science

Provides a detailed explanation of data science perceptions, reinforced by practical examples Presents a road map of future trends suitable for;

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Time Series for Data Science

Practical Time Series Analysis for Data Science is an accessible guide that doesn't require a background in calculus to be engaging;

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Big Data and Social Science

freely available workbooks with data, code, and practical programming exercises, through Binder and GitHub New to the Second Edition;

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Big Data and Social Science

freely available workbooks with data, code, and practical programming exercises, through Binder and GitHub New to the Second Edition;

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Data Science

techniquesEnables the practical use of data science algorithms without the need for programmingDemonstrates processes with;

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A Hands-On Introduction to Data Science

This book introduces the field of data science in a practical and accessible manner, using a hands-on approach that assumes no prior;

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Managing Data Science

management, along with useful tips and best practices to guide you along the way. After understanding the practical applications of data science and;

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Executive Data Science

-earth practical skills that will help you overcome the common challenges that frequently derail data science projects.;

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Data Science from Scratch: First Principles with Python

This is a first-principles-based, practical introduction to the fundamentals of data science aimed at the mathematically-comfortable reader;

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Applying Data Science

This book offers practical guidelines on creating value from the application of data science based on selected artificial intelligence;

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Applying Data Science

This book offers practical guidelines on creating value from the application of data science based on selected artificial intelligence;

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Practical Statistics for Data Scientists

, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's;

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Practical Data Science With R

business questions. Practical Data Science with R lives up to its name. It explains basic principles without the theoretical mumbo-jumbo and jumps;

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Data Alchemy

Beginning with the key challenges that enterprises face in generating value from data, this practical and provocative book systematically;

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Mechanistic Data Science for STEM Education and Applications

) system and design. These data science and mechanistic analysis steps are presented in an intuitive manner that emphasizes practical concepts for;

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Data Science with Java

science applications. With this practical book, Java software engineers looking to add data science skills will take a logical journey through the;

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Data Science & Big Data Analytics

methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any;

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