Description: Deep Learning: A Visual Approach Deep Learning: A Visual Approach No Starch Press ABIS BOOK An accessible, highly-illustrated introduction to deep learning that offers visual and conceptual explanations instead of equations. You'll learn how to use key deep learning algorithms without the need for complex math. Ever since computers began beating us at chess, they've been getting better at a wide range of human activities, from writing songs and generating news articles to helping doctors provide healthcare. Deep learning is the source of many of these breakthroughs, and its remarkable ability to find patterns hiding in data has made it the fastest growing field in artificial intelligence (AI). Digital assistants on our phones use deep learning to understand and respond intelligently to voice commands; automotive systems use it to safely navigate road hazards; online platforms use it to deliver personalized suggestions for movies and books - the possibilities are endless. Deep Learning: A Visual Approach is for anyone who wants to understand this fascinating field in depth, but without any of the advanced math and programming usually required to grasp its internals. If you want to know how these tools work, and use them yourself, the answers are all within these pages. And, if you're ready to write your own programs, there are also plenty of supplemental Python notebooks in the accompanying Github repository to get you going. The book's conversational style, extensive color illustrations, illuminating analogies, and real-world examples expertly explain the key concepts in deep learning, including: ' How text generators create novel stories and articles ' How deep learning systems learn to play and win at human games ' How image classification systems identify objects or people in a photo ' How to think about probabilities in a way that's useful to everyday life ' How to use the machine learning techniques that form the core of modern AI Intellectual adventurers of all kinds can use the powerful ideas covered in Deep Learning: A Visual Approach to build intelligent systems that help us better understand the world and everyone who lives in it. It's the future of AI, and this book allows you to fully envision it. Shipping We offer FREE shipping on specialized orders! We ship within Three business days of payment, usually sooner. We use a selection of shipping services such as UPS, FedEx, USPS etc. We only ship to the lower 48 states, no APO/FPO addresses or PO Boxes allowed. Local pickups and combined shipping options are not provided at this time. Return You can return a product for up to 30 days from the date you purchased it. Any product you return must be in the same condition you received it and in the original packaging. Please keep the receipt. Payment We accept payment by any of the following methods:PayPalPlease pay as soon as possible after winning an auction, as that will allow us to post your item to you sooner!Credit/Debit CardPlease pay within 2 days of buying now, as it makes it easier to ship as fast as possible to you! Feedback Customer satisfaction is very important to us. If you have any problem with your order, please contact us and we will do our best to make you satisfied. Contact Us If you have any queries, please contact us via ebay. We usually respond within 24 hours on weekdays. Please visit our eBay store to check out other items for sale! Thank you for shopping at our store.
Price: 83.01 USD
Location: San Gabriel, California
End Time: 2024-05-07T23:16:36.000Z
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Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
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Color: Multicolor
EAN: 9781718500723
ISBN: 9781718500723
Package Dimensions LxWxH: 9.25x7.13x2.24 Inches
Weight: 3.77 Pounds
MPN: Does not apply
Model: Does not apply
Brand: No Starch Press
Item Length: 9.3in
Item Height: 1.5in
Item Width: 7.1in
Author: Andrew Glassner
Publication Name: Deep Learning : a Visual Approach
Format: Hardcover
Language: English
Publisher: No Starch Press, Incorporated
Publication Year: 2021
Type: Textbook
Item Weight: 59 Oz
Number of Pages: 1200 Pages