Data Engineering for Machine Learning Pipelines: From Python Libraries to ML Pip

Description: Data Engineering for Machine Learning Pipelines by Pavan Kumar Narayanan 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 Dasks 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-time and streaming data engineering pipelines, emphasizing Apache Kafka and workflow orchestration in data engineering. Workflow tools such as Airflow and Prefect are introduced to seamlessly manage and automate complex data workflows.What sets this book apart is its blend of theoretical knowledge and practical application, a structured path from basic to advanced concepts, and insights into using state-of-the-art tools. With this book, you gain access to cutting-edge techniques and insights that are reshaping the industry. This book is not just an educational tool. It is a career catalyst, and an investment in your future as a data engineering expert, poised to meet the challenges of todays data-driven world. What You Will LearnElevate your data wrangling jobs by utilizing the power of both CPU and GPU computing, and learn to process data using Pandas 2.0, Polars, and CuDF at unprecedented speedsDesign data validation pipelines, construct efficient data service APIs, develop real-time streaming pipelines and master the art of workflow orchestration to streamline your engineering projectsLeverage concurrent programming to develop machine learning pipelines and get hands-on experience in development and deployment of machine learning pipelines across AWS, GCP, and Azure Who This Book Is ForData analysts, data engineers, data scientists, machine learning engineers, and MLOps specialists FORMAT Paperback CONDITION Brand New Author Biography Pavan Kumar Narayanan has an extensive and diverse career in the information technology industry, with a primary focus on the data engineering and machine learning domains. Throughout his professional journey, he has consistently delivered solutions in environments characterized by heterogeneity and complexity. His experience spans a broad spectrum, encompassing traditional data warehousing projects following waterfall methodologies and extending to contemporary integrations that involve APIs and message-based systems. Pavan has made substantial contributions to large-scale data integrations for applications in data science and machine learning. At the forefront of these endeavors, he has played a key role in delivering sophisticated data products and solutions, employing a versatile mix of both traditional and agile approaches. Currently employed with Ether Infinitum LLC, Sheridan, WY, Pavan Kumar Narayanan continues to bring his wealth of experience to the forefront of the data engineering and machine learning landscape. Table of Contents Chapter 1: Data Manipulation and Analytics Using Pandas.- Chapter 2: Data Manipulation Using Polars and CuDF.- Chapter 3: Introduction to Data Validation.- Chapter 4: Data Validation Using Great Expectations.- Chapter 5: Introduction to API Design Using FastAPI.- Chapter 6: Introduction to Concurrency Programming Using Task.- Chapter 7: Dask ML.- Module 5: Data Pipelines in the Cloud.- Chapter 9: Introduction to Microsoft Azure.- Chapter 10: Introduction to Google Cloud.- Chapter 11: Introduction to Streaming Data.- Chapter 12: Introduction to Workflow Management Using Airflow.- Chapter 13: Introduction to Workflow Management Using Prefect. Details ISBN Author Pavan Kumar Narayanan Publisher Springer-Verlag Berlin and Heidelberg GmbH & Co. KG ISBN-13 9798868806018 Format Paperback Imprint APress Subtitle From Python Libraries to ML Pipelines and Cloud Platforms Place of Publication Berlin Country of Publication Germany Audience Professional & Vocational Year 2024 UK Release Date 2024-10-17 Pages 636 Illustrations 225 Illustrations, black and white; XXV, 636 p. 225 illus. Publication Date 2024-09-28 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:161599953;

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