Description: Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice. In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation. You'll learn how to: Identify and mitigate common challenges when training, evaluating, and deploying ML models Represent data for different ML model types, including embeddings, feature crosses, and more Choose the right model type for specific problems Build a robust training loop that uses checkpoints, distribution strategy, and hyperparameter tuning Deploy scalable ML systems that you can retrain and update to reflect new data Interpret model predictions for stakeholders and ensure models are treating users fairly 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.
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End Time: 2024-10-04T05:13:02.000Z
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EAN: 9781098115784
ISBN: 9781098115784
Package Dimensions LxWxH: 9.21x6.93x0.94 Inches
Weight: 1.52 Pounds
MPN: Does not apply
Model: Does not apply
Brand: O'Reilly Media
Item Length: 9.1in
Item Height: 0.9in
Item Width: 7in
Author: Sara Robinson, Valliappa Lakshmanan, Michael Munn
Publication Name: Machine Learning Design Patterns : Solutions to Common Challenges in Data Preparation, Model Building, and MLOps
Format: Trade Paperback
Language: English
Publisher: O'reilly, Incorporated
Publication Year: 2020
Type: Textbook
Item Weight: 24.6 Oz
Number of Pages: 405 Pages