Library Of American University Of Madaba
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Prakash, Kolla Bhanu,
Data science handbook : a practical approach / Kolla Bhanu Prakash - Hoboken, NJ : Wiley-Scrivener, 2022. - xiii, 453 p. : ill. (chiefly color) ; 24 cm. - Next-generation computing and communication engineering . - Next-generation computing and communication engineering .
Includes bibliographical references
Available to OhioLINK libraries
Data Science is one of the leading research-driven areas in the modern era. It is having a critical role in healthcare, engineering, education, mechatronics, and medical robotics. Building models and working with data is not value-neutral. We choose the problems with which we work, make assumptions in these models, and decide on metrics and algorithms for the problems. The data scientist identifies the problem which can be solved with data and expert tools of modeling and coding. The book starts with introductory concepts in data science like data munging, data preparation, and transforming data. Chapter 2 discusses data visualization, drawing various plots and histograms. Chapter 3 covers mathematics and statistics for data science. Chapter 4 mainly focuses on machine learning algorithms in data science. Chapter 5 comprises of outlier analysis and DBSCAN algorithm. Chapter 6 focuses on clustering. Chapter 7 discusses network analysis. Chapter 8 mainly focuses on regression and naive-bayes classifier. Chapter 9 covers web-based data visualizations with Plotly. Chapter 10 discusses web scraping. The book concludes with a section discussing 19 projects on various subjects in data science
9781119857334 1119857333 9781119858010 1119858011 1119858003 9781119858003
Big data.
Data mining.
Quantitative research.
Information visualization.
QA76.9.B45 / P73 2022
006.312 / P898
Data science handbook : a practical approach / Kolla Bhanu Prakash - Hoboken, NJ : Wiley-Scrivener, 2022. - xiii, 453 p. : ill. (chiefly color) ; 24 cm. - Next-generation computing and communication engineering . - Next-generation computing and communication engineering .
Includes bibliographical references
Available to OhioLINK libraries
Data Science is one of the leading research-driven areas in the modern era. It is having a critical role in healthcare, engineering, education, mechatronics, and medical robotics. Building models and working with data is not value-neutral. We choose the problems with which we work, make assumptions in these models, and decide on metrics and algorithms for the problems. The data scientist identifies the problem which can be solved with data and expert tools of modeling and coding. The book starts with introductory concepts in data science like data munging, data preparation, and transforming data. Chapter 2 discusses data visualization, drawing various plots and histograms. Chapter 3 covers mathematics and statistics for data science. Chapter 4 mainly focuses on machine learning algorithms in data science. Chapter 5 comprises of outlier analysis and DBSCAN algorithm. Chapter 6 focuses on clustering. Chapter 7 discusses network analysis. Chapter 8 mainly focuses on regression and naive-bayes classifier. Chapter 9 covers web-based data visualizations with Plotly. Chapter 10 discusses web scraping. The book concludes with a section discussing 19 projects on various subjects in data science
9781119857334 1119857333 9781119858010 1119858011 1119858003 9781119858003
Big data.
Data mining.
Quantitative research.
Information visualization.
QA76.9.B45 / P73 2022
006.312 / P898