Maschinelles Lernen für Dummies von Mueller, John Paul, Massaron, Luca
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Maschinelles Lernen für Dummies von Mueller, John Paul, Massaron, Luca
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Artikelmerkmale
- Artikelzustand
- Book Title
- Machine Learning For Dummies
- Genre
- Specialty Boutique
- Topic
- Databases & Big Data
- Narrative Type
- Nonfiction
- Intended Audience
- Adult
- Inscribed
- NO
- ISBN
- 9781119245513
Über dieses Produkt
Product Identifiers
Publisher
Wiley & Sons, Incorporated, John
ISBN-10
1119245516
ISBN-13
9781119245513
eBay Product ID (ePID)
219237562
Product Key Features
Number of Pages
432 Pages
Language
English
Publication Name
Machine Learning for Dummies
Publication Year
2016
Subject
Intelligence (Ai) & Semantics, General, Databases / Data Mining
Type
Textbook
Subject Area
Computers
Format
Trade Paperback
Dimensions
Item Height
0.9 in
Item Weight
20.8 Oz
Item Length
9 in
Item Width
7.1 in
Additional Product Features
Intended Audience
Trade
LCCN
2016-940023
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
006.31
Table Of Content
Introduction 1 Part 1: Introducing How Machines Learn 7 CHAPTER 1: Getting the Real Story about AI 9 CHAPTER 2: Learning in the Age of Big Data 23 CHAPTER 3: Having a Glance at the Future 35 Part 2: Preparing Your Learning Tools 45 CHAPTER 4: Installing an R Distribution 47 CHAPTER 5: Coding in R Using RStudio 63 CHAPTER 6: Installing a Python Distribution 89 CHAPTER 7: Coding in Python Using Anaconda 109 CHAPTER 8: Exploring Other Machine Learning Tools 137 Part 3: Getting Started with the Math Basics 145 CHAPTER 9: Demystifying the Math Behind Machine Learning 147 CHAPTER 10: Descending the Right Curve 167 CHAPTER 11: Validating Machine Learning 181 CHAPTER 12: Starting with Simple Learners 199 Part 4: Learning from Smart and Big Data 217 CHAPTER 13: Preprocessing Data 219 CHAPTER 14: Leveraging Similarity 237 CHAPTER 15: Working with Linear Models the Easy Way 257 CHAPTER 16: Hitting Complexity with Neural Networks 279 CHAPTER 17: Going a Step beyond Using Support Vector Machines 297 CHAPTER 18: Resorting to Ensembles of Learners 315 Part 5: Applying Learning to Real Problems 331 CHAPTER 19: Classifying Images 333 CHAPTER 20: Scoring Opinions and Sentiments 349 CHAPTER 21: Recommending Products and Movies 369 Part 6: The Part of Tens 383 CHAPTER 22: Ten Machine Learning Packages to Master 385 CHAPTER 23: Ten Ways to Improve Your Machine Learning Models 391 INDEX 399
Synopsis
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 invaluable it is. Without machine learning, fraud detection, web search results, real-time ads on web pages, credit scoring, automation, and email spam filtering wouldn't be possible, and this is only showcasing just a few of its capabilities. Written by two data science experts, Machine 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 tasks into a reality. Whether you're maddened by the math behind machine learning, apprehensive about AI, perplexed by preprocessing data--or anything in between--this guide makes it easier to understand and implement machine learning seamlessly. Grasp how day-to-day activities are powered by machine learning Learn to 'speak' certain languages, such as Python and R, to teach machines to perform pattern-oriented tasks and data analysis Learn to code in R using R Studio Find out how to code in Python using Anaconda Dive into this complete beginner's guide so you are armed with all you need to know about machine learning!, Learn how machine learning algorithms are invaluable Implement machine learning in Python and R Use machine learning to accomplish practical tasks Machine learning made easy! It may sound a bit intimidating, but machine learning is an exciting new way to teach your computer to perform all sorts of important and useful tasks. This book is the easy way to get up to speed. It explains how to get started, provides detailed discussions of how the underlying algorithms work, uses languages such as Python and R to make machine learning possible, specifies how to do practical things using common algorithms, and more! Inside The real story about AI R and Python coding The role of statistics Managing big data Demystifying the math Using linear models What neural networks do How to work with images More tools you can use, 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 invaluable it is., 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 invaluable it is. Without machine learning, fraud detection, web search results, real-time ads on web pages, credit scoring, automation, and email spam filtering wouldn't be possible, and this is only showcasing just a few of its capabilities. Written by two data science experts, Machine 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 tasks into a reality. Whether you're maddened by the math behind machine learning, apprehensive about AI, perplexed by preprocessing data--or anything in between--this guide makes it easier to understand and implement machine learning seamlessly. Grasp how day-to-day activities are powered by machine learning Learn to 'speak' certain languages, such as Python and R, to teach machines to perform pattern-oriented tasks and data analysis Learn to code in R using R Studio Find out how to code in Python using Anaconda Dive into this complete beginner's guide so you are armed with all you need to know about machine learning
LC Classification Number
Q325.5
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