







From
To
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.\nAuthor 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 ML-the data. When building systems, you'll move seamlessly from managing incremental datasets for training and\n\nBuilding Machine Learning Systems with a Feature Store\nBatch, Real-Time, and LLM Systems\nFree UK delivery on this item.\n\nThis brand new item is available with free UK delivery using Royal Mail tracked s;
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.\nAuthor 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 ML-the data. When building systems, you'll move seamlessly from managing incremental datasets for training and\n\nBuilding Machine Learning Systems with a Feature Store\nBatch, Real-Time, and LLM Systems\nFree UK delivery on this item.\n\nThis brand new item is available with free UK delivery using Royal Mail tracked s;
Price now:
From
To