Machine Learning For Dummies

Machine Learning For Dummies
Author :
Publisher : John Wiley & Sons
Total Pages : 471
Release :
ISBN-10 : 9781119724018
ISBN-13 : 1119724015
Rating : 4/5 (18 Downloads)

Book Synopsis Machine Learning For Dummies by : John Paul Mueller

Download or read book Machine Learning For Dummies written by John Paul Mueller and published by John Wiley & Sons. This book was released on 2021-02-09 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


Machine Learning For Dummies Related Books

Machine Learning For Dummies
Language: en
Pages: 471
Authors: John Paul Mueller
Categories: Computers
Type: BOOK - Published: 2021-02-09 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

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 ex
Artificial Intelligence For Dummies
Language: en
Pages: 60
Authors: John Paul Mueller
Categories: Computers
Type: BOOK - Published: 2018-03-16 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

Step into the future with AI The term "Artificial Intelligence" has been around since the 1950s, but a lot has changed since then. Today, AI is referenced in th
Coding with AI For Dummies
Language: en
Pages: 343
Authors: Chris Minnick
Categories: Computers
Type: BOOK - Published: 2024-02-23 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

Boost your coding output and accuracy with artificial intelligence tools Coding with AI For Dummies introduces you to the many ways that artificial intelligence
Enterprise AI For Dummies
Language: en
Pages: 359
Authors: Zachary Jarvinen
Categories: Business & Economics
Type: BOOK - Published: 2020-08-17 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

Master the application of artificial intelligence in your enterprise with the book series trusted by millions In Enterprise AI For Dummies, author Zachary Jarvi
Deep Learning for Coders with fastai and PyTorch
Language: en
Pages: 624
Authors: Jeremy Howard
Categories: Computers
Type: BOOK - Published: 2020-06-29 - Publisher: O'Reilly Media

DOWNLOAD EBOOK

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with