书目名称 | Data Engineering for Machine Learning Pipelines | 副标题 | From Python Librarie | 编辑 | Pavan Kumar Narayanan | 视频video | | 概述 | Covers the A to Z of data engineering for ML pipelines, including data wrangling and cloud computing.Provides you with the latest technologies and methodologies, to move through the next decade of dat | 图书封面 |  | 描述 | .This book covers modern data engineering functions and important Python libraries, to help you develop state-of-the-art ML pipelines and integration code...The book begins by explaining data analytics and transformation, delving into the Pandas library, its capabilities, and nuances. It then explores emerging libraries such as Polars and CuDF, providing insights into GPU-based computing and cutting-edge data manipulation techniques. The text discusses the importance of data validation in engineering processes, introducing tools such as Great Expectations and Pandera to ensure data quality and reliability. The book delves into API design and development, with a specific focus on leveraging the power of FastAPI. It covers authentication, authorization, and real-world applications, enabling you to construct efficient and secure APIs using FastAPI. Also explored is concurrency in data engineering, examining Dask‘s capabilities from basic setup to crafting advanced machine learning pipelines. The book includes development and delivery of data engineering pipelines using leading cloud platforms such as AWS, Google Cloud, and Microsoft Azure. The concluding chapters concentrate on real-t | 出版日期 | Book 2024 | 关键词 | Artificial Intelligence; Machine Learning; Python; MLOps; Data Engineering; DevOps; Data Analytics; API Des | 版次 | 1 | doi | https://doi.org/10.1007/979-8-8688-0602-5 | isbn_softcover | 979-8-8688-0601-8 | isbn_ebook | 979-8-8688-0602-5 | copyright | Pavan Kumar Narayanan 2024 |
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