menu
{ "item_title" : "Data Engineering and Data Science", "item_author" : [" Kukatlapalli Pradeep Kumar", "Aynur Unal", "Vinay Jha Pillai "], "item_description" : "DATA ENGINEERING and DATA SCIENCEWritten and edited by one of the most prolific and well-known experts in the field and his team, this exciting new volume is the one-stop shop for the concepts and applications of data science and engineering for data scientists across many industries.The field of data science is incredibly broad, encompassing everything from cleaning data to deploying predictive models. However, it is rare for any single data scientist to be working across the spectrum day to day. Data scientists usually focus on a few areas and are complemented by a team of other scientists and analysts. Data engineering is also a broad field, but any individual data engineer doesn't need to know the whole spectrum of skills. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there have to be mechanisms for collecting and validating that information.In this exciting new volume, the team of editors and contributors sketch the broad outlines of data engineering, then walk through more specific descriptions that illustrate specific data engineering roles. Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This book brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/1/11/984/187/1119841879_b.jpg", "price_data" : { "retail_price" : "225.00", "online_price" : "225.00", "our_price" : "225.00", "club_price" : "225.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Data Engineering and Data Science|Kukatlapalli Pradeep Kumar

Data Engineering and Data Science : Concepts and Applications

local_shippingShip to Me
On Order. Usually ships in 2-4 weeks
FREE Shipping for Club Members help

Overview

DATA ENGINEERING and DATA SCIENCE

Written and edited by one of the most prolific and well-known experts in the field and his team, this exciting new volume is the "one-stop shop" for the concepts and applications of data science and engineering for data scientists across many industries.

The field of data science is incredibly broad, encompassing everything from cleaning data to deploying predictive models. However, it is rare for any single data scientist to be working across the spectrum day to day. Data scientists usually focus on a few areas and are complemented by a team of other scientists and analysts. Data engineering is also a broad field, but any individual data engineer doesn't need to know the whole spectrum of skills. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there have to be mechanisms for collecting and validating that information.

In this exciting new volume, the team of editors and contributors sketch the broad outlines of data engineering, then walk through more specific descriptions that illustrate specific data engineering roles. Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This book brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.

This item is Non-Returnable

Details

  • ISBN-13: 9781119841876
  • ISBN-10: 1119841879
  • Publisher: Wiley-Scrivener
  • Publish Date: September 2023
  • Dimensions: 9.1 x 6.25 x 0.97 inches
  • Shipping Weight: 1.75 pounds
  • Page Count: 464

Related Categories

You May Also Like...

    1

BAM Customer Reviews