【智能技术，Springer 数据科学】Intelligent Techniques for Data Science (2016)

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Intelligent Techniques for Data Science

Authors: Rajendra Akerkar, Priti Srinivas Sajja



Focuses on methods significantly beneficial in data science, and clearly describes them at an introductory level, with extensions to selected intermediate and advanced techniques

Reinforces the machine learning principles with necessary demonstrations in the field of data science

Integrates illustrations, cases and examples to support pedagogical exposition

Equips readers with the necessary information to obtain hands‐on experience of data science

This textbook provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. These embrace the family of neural networks, fuzzy systems and evolutionary computing in addition to other fields within machine learning, and will help in identifying, visualizing, classifying and analyzing data to support business decisions.

The authors, discuss advantages and drawbacks of different approaches, and present a sound foundation for the reader to design and implement data analytic solutions for real‐world applications in an intelligent manner. Intelligent Techniques for Data Science also provides real-world cases of extracting value from data in various domains such as retail, health, aviation, telecommunication and tourism.

Table of contents

Front Matter
Pages i-xvi

Introduction to Data Science
Pages 1-30

Data Analytics
Pages 31-52

Basic Learning Algorithms
Pages 53-93

Fuzzy Logic
Pages 95-123

Artificial Neural Network
Pages 125-155

Genetic Algorithms and Evolutionary Computing
Pages 157-184

Other Metaheuristics and Classification Approaches
Pages 185-209

Analytics and Big Data
Pages 211-236

Data Science Using R
Pages 237-259

Back Matter
Pages 261-272

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关键词：Data Science Intelligent Techniques Technique Springer principles necessary describes learning examples

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Good book.

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篇学术的书籍吧