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Machine Learning For Dummies

BuchKartoniert, Paperback
464 Seiten
Englisch
Wiley & Sonserschienen am08.04.20212. Aufl.
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 learningWork with Python 3.8 and TensorFlow 2.x (and R as a download)Build and test your own modelsUse the latest datasets, rather than the worn out data found in other booksApply 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.mehr
Verfügbare Formate
BuchKartoniert, Paperback
EUR33,50
E-BookPDF2 - DRM Adobe / Adobe Ebook ReaderE-Book
EUR22,99
E-BookEPUB2 - DRM Adobe / EPUBE-Book
EUR22,99

Produkt

KlappentextOne 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 learningWork with Python 3.8 and TensorFlow 2.x (and R as a download)Build and test your own modelsUse the latest datasets, rather than the worn out data found in other booksApply 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.
Details
ISBN/GTIN978-1-119-72401-8
ProduktartBuch
EinbandartKartoniert, Paperback
Erscheinungsjahr2021
Erscheinungsdatum08.04.2021
Auflage2. Aufl.
ReiheFor Dummies
Seiten464 Seiten
SpracheEnglisch
Gewicht834 g
Artikel-Nr.56263704

Inhalt/Kritik

Inhaltsverzeichnis
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   431mehr

Autor

John Mueller has produced hundreds of books and articles on topics ranging from networking to home security and from database management to heads-down programming.Luca Massaron is a senior expert in data science who has been involved with quantitative methods since 2000. He is a Google Developer Expert (GDE) in machine learning.