Bộ sách luyện thi ETS 2023 LC&RC
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299,000₫
Machine Learning Design Patterns Solutions to Common (Sách keo gáy, bìa mềm)
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
Categories:Computers - Computer Science
Year:2020
Edition:1
Language:english
Pages:408
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