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Machine learning for dummies

Author: John Mueller; Luca Massaron
Publisher: Hoboken, NJ : John Wiley & Sons, Inc., [2016] ©2016
Series: --For dummies.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
AYour no-nonsense guide to making sense of machine learningMachine Learning For Dummies offers a much-needed entry point for anyone looking to use machine learning to accomplish practical tasks. Covering the entry-level topics needed to get you familiar with the basic concepts of machine learning, this guide quickly helps you make sense of the programming languages and tools you need to turn machine learning-based  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Mueller, John Paul.
Machine learning for dummies.
Hoboken, New Jersey : John Wiley & Sons, Inc., ©2016
xii, 410 pages
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: John Mueller; Luca Massaron
ISBN: 9781119245759 1119245753 9781119245773 111924577X
OCLC Number: 949758901
Description: 1 online resource.
Contents: Title Page --
Copyright Page --
Table of Contents --
Introduction --
About This Book --
Foolish Assumptions --
Icons Used in This Book --
Beyond the Book --
Where to Go from Here --
Part 1 Introducing How Machines Learn --
Chapter 1 Getting the Real Story about AI --
Moving beyond the Hype --
Dreaming of Electric Sheep --
Understanding the history of AI and machine learning --
Exploring what machine learning can do for AI --
Considering the goals of machine learning --
Defining machine learning limits based on hardware --
Overcoming AI Fantasies. Discovering the fad uses of AI and machine learning --
Considering the true uses of AI and machine learning --
Being useful --
being mundane --
Considering the Relationship between AI and Machine Learning --
Considering AI and Machine Learning Specifications --
Defining the Divide between Art and Engineering --
Chapter 2 Learning in the Age of Big Data --
Defining Big Data --
Considering the Sources of Big Data --
Building a new data source --
Using existing data sources --
Locating test data sources --
Specifying the Role of Statistics in Machine Learning --
Understanding the Role of Algorithms. Defining what algorithms do --
Considering the five main techniques --
Defining What Training Means --
Chapter 3 Having a Glance at the Future --
Creating Useful Technologies for the Future --
Considering the role of machine learning in robots --
Using machine learning in health care --
Creating smart systems for various needs --
Using machine learning in industrial settings --
Understanding the role of updated processors and other hardware --
Discovering the New Work Opportunities with Machine Learning --
Working for a machine --
Working with machines --
Repairing machines. Creating new machine learning tasks --
Devising new machine learning environments --
Avoiding the Potential Pitfalls of Future Technologies --
Part 2 Preparing Your Learning Tools --
Chapter 4 Installing an R Distribution --
Choosing an R Distribution with Machine Learning in Mind --
Installing R on Windows --
Installing R on Linux --
Installing R on Mac OS X --
Downloading the Datasets and Example Code --
Understanding the datasets used in this book --
Defining the code repository --
Chapter 5 Coding in R Using RStudio --
Understanding the Basic Data Types --
Working with Vectors. Organizing Data Using Lists --
Working with Matrices --
Creating a basic matrix --
Changing the vector arrangement --
Accessing individual elements --
Naming the rows and columns --
Interacting with Multiple Dimensions Using Arrays --
Creating a basic array --
Naming the rows and columns --
Creating a Data Frame --
Understanding factors --
Creating a basic data frame --
Interacting with data frames --
Expanding a data frame --
Performing Basic Statistical Tasks --
Making decisions --
Working with loops --
Performing looped tasks without loops --
Working with functions --
Finding mean and median.
Series Title: --For dummies.
Responsibility: by John Paul Mueller and Luca Massaron.

Abstract:

Your no-nonsense guide to making sense of machine learning Machine learning can be a mind-boggling concept for the masses, but those who are in the trenches of computer programming know just how  Read more...

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"Comprehensive and not just for dummies." (MagPi, January 2017)

 
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