Search Torrents
|
Browse Torrents
|
48 Hour Uploads
|
TV shows
|
Music
|
Top 100
Audio
Video
Applications
Games
Porn
Other
All
Music
Audio books
Sound clips
FLAC
Other
Movies
Movies DVDR
Music videos
Movie clips
TV shows
Handheld
HD - Movies
HD - TV shows
3D
Other
Windows
Mac
UNIX
Handheld
IOS (iPad/iPhone)
Android
Other OS
PC
Mac
PSx
XBOX360
Wii
Handheld
IOS (iPad/iPhone)
Android
Other
Movies
Movies DVDR
Pictures
Games
HD - Movies
Movie clips
Other
E-books
Comics
Pictures
Covers
Physibles
Other
Details for:
Narayanan P. Data Engineering for Machine Learning Pipelines. From Python...2024
narayanan p data engineering machine learning pipelines from python 2024
Type:
E-books
Files:
1
Size:
33.0 MB
Uploaded On:
Sept. 30, 2024, 8:10 a.m.
Added By:
andryold1
Seeders:
6
Leechers:
5
Info Hash:
74CB857BFD69FB0AF2F7F2C9FB2B2DBCCB6825D6
Get This Torrent
Textbook in PDF format 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-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 today's data-driven world. What You Will Learn Elevate 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 speeds. Design data validation pipelines, construct efficient data service APIs, develop real-time streaming pipelines and master the art of workflow orchestration to streamline your engineering projects. Leverage 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 For Data analysts, data engineers, data scientists, machine learning engineers, and MLOps specialists
Get This Torrent
Narayanan P. Data Engineering for Machine Learning Pipelines. From Python...2024.pdf
33.0 MB
