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Machine learning for dummies /
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, t...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, NJ :
John Wiley & Sons, Inc.,
[2016]
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| Colección: | --For dummies.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
Tabla de Contenidos:
- 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.