Building Machine Learning Systems with a Feature Store (Early Rel...

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Infohash : 6D9E54F42F16A8E84791B7FA20B2BDD44AE25865



Building Machine Learning Systems with a Feature Store (Early Release)



https://DevCourseWeb.com

2024 | English | 9781098165222 | EPUB | 39 pages | 4.22 MB

Get up to speed on a new unified approach to building machine learning (ML) systems with batch data, real-time data, and large language models (LLMs) based on independent, modular ML pipelines and a shared data layer. With this practical book, data scientists and ML engineers will learn in detail how to develop, maintain, and operate modular ML systems.

Author Jim Dowling introduces fundamental MLOps principles and practices for developing and operating reliable ML systems and describes the key data platform that you'll use to build and operate your ML systems: the feature store. Through examples, you'll look at how the feature store helps solve the hardest problem in MLβ€”the data. When building systems, you'll move seamlessly from managing incremental datasets for training and fine-tuning to real-time data access and retrieval-augmented generation for online ML systems.

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[ DevCourseWeb.com ] Building Machine Learning Systems with a Feature Store (Early Release)
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    • BuildingMachineLearningSystemswithaFeatureStore.epub (4.2 MB)

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