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Machine Learning For Dummies

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Last updated on Jun 13, 2024 13:25:04 PDTView all revisionsView all revisions

Item specifics

Condition
Acceptable: A book with obvious wear. May have some damage to the cover but integrity still intact. ...
Release Year
2021
Book Title
Machine Learning For Dummies
ISBN
9781119724018
Subject Area
Computers, Science
Publication Name
Machine Learning for Dummies
Item Length
9.1 in
Publisher
Wiley & Sons, Incorporated, John
Subject
Expert Systems, General, Databases / Data Mining
Publication Year
2021
Type
Textbook
Format
Trade Paperback
Language
English
Item Height
1.2 in
Author
John Paul Mueller, Luca Massaron
Item Width
7.3 in
Item Weight
22.4 Oz
Number of Pages
464 Pages

About this product

Product Information

One of Mark Cuban's top reads for better understanding A.I. (inc.com, 2021) Your comprehensive entry-level guide to machine learning While machine learning expertise doesn't quite mean you can create your own Turing Test-proof android--as in the movie Ex Machina--it is a form of artificial intelligence and one of the most exciting technological means of identifying opportunities and solving problems fast and on a large scale. Anyone who masters the principles of machine learning is mastering a big part of our tech future and opening up incredible new directions in careers that include fraud detection, optimizing search results, serving real-time ads, credit-scoring, building accurate and sophisticated pricing models--and way, way more. Unlike most machine learning books, the fully updated 2nd Edition of Machine Learning For Dummies doesn't assume you have years of experience using programming languages such as Python (R source is also included in a downloadable form with comments and explanations), but lets you in on the ground floor, covering the entry-level materials that will get you up and running building models you need to perform practical tasks. It takes a look at the underlying--and fascinating--math principles that power machine learning but also shows that you don't need to be a math whiz to build fun new tools and apply them to your work and study. Understand the history of AI and machine learning Work with Python 3.8 and TensorFlow 2.x (and R as a download) Build and test your own models Use the latest datasets, rather than the worn out data found in other books Apply machine learning to real problems Whether you want to learn for college or to enhance your business or career performance, this friendly beginner's guide is your best introduction to machine learning, allowing you to become quickly confident using this amazing and fast-developing technology that's impacting lives for the better all over the world.

Product Identifiers

Publisher
Wiley & Sons, Incorporated, John
ISBN-10
1119724015
ISBN-13
9781119724018
eBay Product ID (ePID)
11050081110

Product Key Features

Author
John Paul Mueller, Luca Massaron
Publication Name
Machine Learning for Dummies
Format
Trade Paperback
Language
English
Subject
Expert Systems, General, Databases / Data Mining
Publication Year
2021
Type
Textbook
Subject Area
Computers, Science
Number of Pages
464 Pages

Dimensions

Item Length
9.1 in
Item Height
1.2 in
Item Width
7.3 in
Item Weight
22.4 Oz

Additional Product Features

Edition Number
2
LCCN
2020-952332
Intended Audience
Trade
Lc Classification Number
Q325.5
Table of Content
Introduction 1 Part 1: Introducing How Machines Learn 5 Chapter 1: Getting the Real Story about AI 7 Chapter 2: Learning in the Age of Big Data 23 Chapter 3: Having a Glance at the Future 37 Part 2: Preparing Your Learning Tools 47 Chapter 4: Installing a Python Distribution 49 Chapter 5: Beyond Basic Coding in Python 67 Chapter 6: Working with Google Colab 87 Part 3: Getting Started with the Math Basics 115 Chapter 7: Demystifying the Math Behind Machine Learning 117 Chapter 8: Descending the Gradient 139 Chapter 9: Validating Machine Learning 153 Chapter 10: Starting with Simple Learners 175 Part 4: Learning from Smart and Big Data 197 Chapter 11: Preprocessing Data 199 Chapter 12: Leveraging Similarity 221 Chapter 13: Working with Linear Models the Easy Way 243 Chapter 14: Hitting Complexity with Neural Networks 271 Chapter 15: Going a Step Beyond Using Support Vector Machines 307 Chapter 16: Resorting to Ensembles of Learners 319 Part 5: Applying Learning to Real Problems 339 Chapter 17: Classifying Images 341 Chapter 18: Scoring Opinions and Sentiments 361 Chapter 19: Recommending Products and Movies 383 Part 6: The Part of Tens 405 Chapter 20: Ten Ways to Improve Your Machine Learning Models 407 Chapter 21: Ten Guidelines for Ethical Data Usage 415 Chapter 22: Ten Machine Learning Packages to Master 423 Index 431
Copyright Date
2021
Dewey Decimal
006.31
Dewey Edition
23
Illustrated
Yes

Item description from the seller

Dream Books Co.

Dream Books Co.

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