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Machine Learning Design Patterns

By Valliappa Lakshmanan

Machine Learning Design Patterns Computer Science

Machine Learning Design Patterns

Only 1 item left in stock
Description
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
Product details
Binding:
Paperback
Edition:
1
Number of Pages:
405
Release Date:
2020-11-03
Publication Date:
2020-10-31
Publisher:
O'Reilly Media
Languages:
Original: English
ISBN10:
1098115783
ISBN13:
9781098115784
GPSR Manufacturer Reference:
[email protected]
Weight:
700 g
Height:
177 cm
Width:
233 cm
Thickness:
27 cm

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Very good
Almost no signs of wear. Book pages have no markings, accessories are intact and all other media are in good condition.
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