Data engineering and data science : concepts and applications
tarafından
 
Kumar, Kukatlapalli Pradeep, editor.

Başlık
Data engineering and data science : concepts and applications

Yazar
Kumar, Kukatlapalli Pradeep, editor.

ISBN
9781119841999
 
9781119841982
 
9781119841975

Fiziksel Tanımlama
1 online resource : illustrations.

Seri
Advances in data engineering and machine learning
 
Advances in data engineering and machine learning.

İçerik
Front Matter -- Quality Assurance in Data Science / KS Jasmine, D K Ajay, Aditya Raj -- Design and Implementation of Social Media Mining - Knowledge Discovery Methods for Effective Digital Marketing Strategies / Prashant Bhat, Pradnya Malaganve -- A Study on Big Data Engineering Using Cloud Data Warehouse / T N Manjunath, S K Pushpa, Ravindra S Hegadi, K S Ananya Hathwar -- Data Mining with Cluster Analysis Through Partitioning Approach of Huge Transaction Data / K Sampath Kini, BH Karthik Pai -- Application of Data Science in Macromodeling of Nonlinear Dynamical Systems / S Nagaraj, D Seshachalam, G Jayalatha -- Comparative Analysis of Various Ensemble Approaches for Web Page Classification / J Dutta, Yong Woon Kim, Dalia Dominic -- Feature Engineering and Selection Approach Over Malicious Image / PM Kavitha, B Muruganantham -- Cubic-Regression and Likelihood Based Boosting GAM to Model Drug Sensitivity for Glioblastoma / Satyawant Kumar, Vinai George Biju, Ho-Kyoung Lee, Blessy Baby Mathew -- Unobtrusive Engagement Detection through Semantic Pose Estimation and Lightweight ResNet for an Online Class Environment / Michael Moses Thiruthuvanathan, Balachandran Krishnan, Madhavi Rangaswamy -- Building Rule Base for Decision Making - A Fuzzy-Rough Approach / M K Sabu, M S Neeraj Krishna, R Reshmi -- An Effective Machine Learning Approach to Model Healthcare Data / Shaila H Koppad, S Anupama Kumar, Mohan Kumar -- Recommendation Engine for Retail Domain Using Machine Learning Techniques / K T Chandrashekhara, C N Gireesh Babu, M Thungamani -- Mining Heterogeneous Lung Cancer from Computer Tomography (CT) Scan with the Confusion Matrix / Denny Dominic, Krishnan Balachandran -- ML Algorithms and Their Approach on COVID-19 Data Analysis / Kambaluru Ashok, Penumalli Anvesh Reddy, Kukatlapalli Pradeep Kumar -- Analysis and Design for the Early Stage Detection of Lung Diseases Using Machine Learning Algorithms / Sindhu Madhuri, T R Mahesh, V Vivek, H K Shashikala, C Saravanan -- Estimation of Cancer Risk through Artificial Neural Network / K Aditya Shastry, H A Sanjay, N Balaji, B H Karthik Pai -- Applications and Advancements in Data Science and Analytics / T Mamatha, A Balaram, B Rama Subba Reddy, C Shoba Bindu, M Niranjanamurthy -- About the Editors -- Index -- Also of Interest

Özet
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.

Notlar
John Wiley and Sons

Konu Terimleri
Information technology.
 
Technologie de l'information.
 
Probability & Statistics.
 
MATHEMATICS.
 
Information technology. (OCoLC)fst00973089

Tür
Electronic books.

Yazar Ek Girişi
Kumar, Kukatlapalli Pradeep,

Elektronik Erişim
https://onlinelibrary.wiley.com/doi/book/10.1002/9781119841999


KütüphaneMateryal TürüDemirbaş NumarasıYer Numarası[[missing key: search.ChildField.HOLDING]]Durumu/İade Tarihi
Çevrimiçi KütüphaneE-Kitap598563-1001T58.5 .D38 2023Wiley E-Kitap Koleksiyonu