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The design patterns on this e-book seize greatest practices and options to recurring issues in machine studying. The authors, three Google engineers, catalog confirmed strategies to assist knowledge scientists deal with widespread issues all through the ML course of. These design patterns codify the expertise of lots of of specialists into simple, approachable recommendation.
On this e-book, you’ll discover detailed explanations of 30 patterns for knowledge and drawback illustration, operationalization, repeatability, reproducibility, flexibility, explainability, and equity. Every sample features a description of the issue, a wide range of potential options, and suggestions for selecting the very best method to your scenario.
You may discover ways to:
Determine and mitigate widespread challenges when coaching, evaluating, and deploying ML fashions Characterize knowledge for various ML mannequin varieties, together with embeddings, characteristic crosses, and extra Select the appropriate mannequin sort for particular issues Construct a sturdy coaching loop that makes use of checkpoints, distribution technique, and hyperparameter tuning Deploy scalable ML methods that you would be able to retrain and replace to mirror new knowledge Interpret mannequin predictions for stakeholders and guarantee fashions are treating customers pretty
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Writer : O’Reilly Media
Publication date : Nov. 24 2020
Version : 1st
Language : English
Print size : 405 pages
ISBN-10 : 1098115783
ISBN-13 : 978-1098115784
Merchandise weight : 1.05 kg
Dimensions : 23.01 x 2.39 x 17.4 cm
Greatest Sellers Rank: #260,001 in Books (See Prime 100 in Books) #57 in Machine Principle #70 in AI Pc Arithmetic #75 in AI Principle of Computing
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