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Deep Learning with PyTorch: Build, train, and tune neural networks using Python

Description: payment | shipping rates | returns Deep Learning with PyTorch: Build, train, and tune neural networks using Python Product Category : Book ISBN-13 : 9781617295263 Title : Deep Learning with PyTorch: Build, train, and tune neural networks using Python Authors : Stevens, Eli Condition : Used - Very Good The cover is clean but does show some wear. About Goodwill of San Francisco Goodwill equips low-income individuals and those with barriers with the skills required to succeed in the 21st century job market. We also hire our trainees to gain transferable skills and valuable on-the-job experience in our stores and warehouses. And for those motivated job seekers who want to pursue a sustainable career track, we help place them in jobs at top Bay Area companies. Payment We ship via multiple carriers. Order are shipped via economy services. Transit times may vary from 4-10 business days to arrive once the order has been shipped. We do not ship internationally. Orders typically ship within 1-3 business days. We strive to get out all orders as soon as possible! Returns We do not accept returns on any order. Should there be any discrepancy issues with your order, please contact us via the methods available within eBay regarding any problems before leaving negative feedback. Any defects, damages, or material differences with your item, must be reported to us within 14 days from the day received. © 2021 Goodwill of San Francisco

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Location: South San Francisco, California

End Time: 2025-02-08T16:50:30.000Z

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Deep Learning with PyTorch: Build, train, and tune neural networks using Python

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Number of Pages: 450 Pages

Publication Name: Deep Learning with Pytorch

Language: English

Publisher: Manning Publications Co. LLC

Subject: Machine Theory, Intelligence (Ai) & Semantics, General, Data Processing

Item Height: 1.1 in

Publication Year: 2020

Item Weight: 31.7 Oz

Type: Textbook

Author: Luca Antiga, Eli Stevens

Item Length: 9.3 in

Subject Area: Mathematics, Computers

Item Width: 7.3 in

Format: Trade Paperback

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