Python Design Patterns For Machine Learning
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Machine Learning Design Patterns
Author: Valliappa Lakshmanan
language: en
Publisher: O'Reilly Media
Release Date: 2020-10-15
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
Deep Learning Design Patterns
Author: Andrew Ferlitsch
language: en
Publisher: Manning Publications
Release Date: 2021-05-25
Deep Learning Design Patterns distills models from the latest research papers into practical design patterns applicable to enterprise AI projects. You'll learn how to integrate design patterns into deep learning systems from some amazing examples, using diagrams, code samples, and easy-to-understand language. Deep learning has revealed ways to create algorithms for applications that we never dreamed were possible. For software developers, the challenge lies in taking cutting-edge technologies from R&D labs through to production. Deep Learning Design Patterns, is here to help. In it, you'll find deep learning models presented in a unique new way: as extendable design patterns you can easily plug-and-play into your software projects. Deep Learning Design Patterns distills models from the latest research papers into practical design patterns applicable to enterprise AI projects. You'll learn how to integrate design patterns into deep learning systems from some amazing examples, using diagrams, code samples, and easy-to-understand language. Building on your existing deep learning knowledge, you'll quickly learn to incorporate the very latest models and techniques into your apps as idiomatic, composable, and reusable design patterns. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Python 3 Object Oriented Programming
Author: Dusty Phillips
language: en
Publisher: Packt Publishing Ltd
Release Date: 2010-07-26
Harness the power of Python 3 objects.