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Fundamentals of Machine Learning for Predictive Data Analytics  second edition
  • Author : John D. Kelleher,Brian Mac Namee,Aoife D'Arcy
  • Publisher : MIT Press
  • Release Date : 2020-10-20

The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment,

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Fundamentals of Machine Learning for Predictive Data Analytics
  • Author : John D. Kelleher,Brian Mac Namee,Aoife D'Arcy
  • Publisher : MIT Press
  • Release Date : 2015-07-24

A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.

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Fundamentals of Machine Learning for Predictive Data Analytics
  • Author : John D. Kelleher,Brian Mac Namee,Aoife D'Arcy
  • Publisher : MIT Press
  • Release Date : 2015-07-31

A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk

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Machine Learning Techniques for Multimedia
  • Author : Matthieu Cord,Pádraig Cunningham
  • Publisher : Springer Science & Business Media
  • Release Date : 2008-02-07

Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it. Arising from the EU

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Mastering Machine Learning with Python in Six Steps
  • Author : Manohar Swamynathan
  • Publisher : Apress
  • Release Date : 2019-10-01

Explore fundamental to advanced Python 3 topics in six steps, all designed to make you a worthy practitioner. This updated version’s approach is based on the “six degrees of separation” theory, which states that everyone and everything is a maximum of six steps away and presents each topic in two

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Deep Learning
  • Author : John D. Kelleher
  • Publisher : MIT Press
  • Release Date : 2019-09-10

An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products from

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Fundamentals of Predictive Analytics with JMP  Second Edition
  • Author : Ron Klimberg,B. D. McCullough
  • Publisher : SAS Institute
  • Release Date : 2017-12-19

Written for students in undergraduate and graduate statistics courses, as well as for the practitioner who wants to make better decisions from data and models, this updated and expanded second edition of Fundamentals of Predictive Analytics with JMP(R) bridges the gap between courses on basic statistics, which focus on

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Predictive Analytics with Microsoft Azure Machine Learning
  • Author : Valentine Fontama,Roger Barga,Wee Hyong Tok
  • Publisher : Apress
  • Release Date : 2014-11-25

Data Science and Machine Learning are in high demand, as customers are increasingly looking for ways to glean insights from all their data. More customers now realize that Business Intelligence is not enough as the volume, speed and complexity of data now defy traditional analytics tools. While Business Intelligence addresses

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Data Science
  • Author : Vijay Kotu,Bala Deshpande
  • Publisher : Morgan Kaufmann
  • Release Date : 2018-11-27

Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform. Whether you are brand new to data science or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important

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The Elements of Statistical Learning
  • Author : Trevor Hastie,Robert Tibshirani,Jerome Friedman
  • Publisher : Springer Science & Business Media
  • Release Date : 2013-11-11

During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the

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Fundamentals of Predictive Text Mining
  • Author : Sholom M. Weiss,Nitin Indurkhya,Tong Zhang
  • Publisher : Springer
  • Release Date : 2015-09-07

This successful textbook on predictive text mining offers a unified perspective on a rapidly evolving field, integrating topics spanning the varied disciplines of data science, machine learning, databases, and computational linguistics. Serving also as a practical guide, this unique book provides helpful advice illustrated by examples and case studies. This

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Data Mining  Practical Machine Learning Tools and Techniques
  • Author : Ian H. Witten,Eibe Frank,Mark A. Hall
  • Publisher : Elsevier
  • Release Date : 2011-02-03

Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine

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Predictive Analytics
  • Author : Dursun Delen
  • Publisher : FT Press Analytics
  • Release Date : 2020-10-30

In Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners, Dr. Dursun Delen illuminates state-of-the-art best practices for predictive analytics for students. Using predictive analytics techniques, students can uncover hidden patterns and correlations in their data, and leverage this insight to improve a wide range of business decisions.

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Machine Learning
  • Author : Peter Flach
  • Publisher : Cambridge University Press
  • Release Date : 2012-09-20

Covering all the main approaches in state-of-the-art machine learning research, this will set a new standard as an introductory textbook.

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Introduction to Data Science
  • Author : Rafael A. Irizarry
  • Publisher : CRC Press
  • Release Date : 2019-11-20

Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization,

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