Description: About this Item The item is a book Paperback The Author Name is Jeremy Howard The Title is Deep Learning for Coders with fastai and PyTorch : AI Applications Without a PhD Condition New Other Comments Pages Count - 621. Category - Computers Product Description - 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 Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You'll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filteringLearn the latest deep learning techniques that matter most in practiceImprove accuracy, speed, and reliability by understanding how deep learning models workDiscover how to turn your models into web applicationsImplement deep learning algorithms from scratchConsider the ethical implications of your workGain insight from the foreword by PyTorch cofounder, Soumith Chintala We Use Stock Images Because we have over 2 million items for sale we have to use stock images, this listing does not include the actual image of the item for sale. The purchase of this specific item is made with the understanding that the image shown in this listing is a stock image and not the actual item for sale. For example: some of our stock images include stickers, labels, price tags, hyper stickers, obi's, promotional messages, signatures and or writing which may not be available in the actual item. When possible we will add details of the items we are selling to help buyers know what is included in the item for sale. The details are provided automatically from our central master database and can sometimes be wrong. Books are released in many editions and variations, such as standard edition, re-issue, not for sale, promotional, special edition, limited edition, and many other editions and versions. The Book you receive could be any of these editions or variations. If you are looking for a specific edition or version please contact us to verify what we are selling. Gift IdeasThis is a great Christmas gift idea. Hours of ServiceWe have many warehouses, some of the warehouses process orders seven days a week, but the Administration Support Staff are located at a head office location, outside of the warehouses, and typically work only Monday to Friday. Location ID 9000z iHaveit SKU ID 167505102
Price: 108.91 USD
Location: US
End Time: 2024-11-22T12:33:30.000Z
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Restocking Fee: No
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All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
Fiction/Non-Fiction: Non-Fiction
Genre/Subject: Computers
Brand: O'Reilly Media, Inc, USA
Weight: 0.93
Style: NA
Title: Deep Learning for Coders with fastai and PyTorch AI Application
Release Title: Deep Learning for Coders with fastai and PyTorch AI Application
Record Grading: New
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Film/TV Title: Deep Learning for Coders with fastai and PyTorch AI Applicatio
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Movie/TV Title: Deep Learning for Coders with fastai and PyTorch AI Applicatio
UPC: 9781492045526
EAN: 9781492045526
ISBN: 9781492045526
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Metal: NA
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Model: NA
Number of Pages: 621 Pages
Language: English
Publication Name: Deep Learning for Coders with Fastai and Pytorch : Ai Applications Without a Phd
Publisher: O'reilly Media, Incorporated
Item Height: 1.5 in
Publication Year: 2020
Subject: Programming / General, Machine Theory, Image Processing, Computer Science, Neural Networks, Data Visualization, Programming Languages / Python
Item Weight: 38.2 Oz
Type: Textbook
Subject Area: Computers
Item Length: 9.2 in
Author: Jeremy Howard, Sylvain Gugger
Item Width: 7 in
Format: Trade Paperback
