In this comprehensive guide, we delve into the world of data science, machine learning, and AI modeling, providing readers with a robust foundation and practical skills to tackle real-world problems....Loe edasi...
The book provides a foundational guide to statistical computing and visualisation Using R programming with an emphasis on practical data analysis skills that are directly applicable to diverse fields like finance, defence, health, and education....Loe edasi...
Machine learning has redefined the way we work with data and is increasingly becoming an indispensable part of everyday life, yet software engineering has played a remarkably small role compared to other disciplines. This book addresses such a dispa...Loe edasi...
Applied Statistics with Python concentrates on applied and computational aspects of statistics, focussing on conceptual understanding and Python-based calculations. It compiles multiple aspects of applied statistics, teaching useful skills in statis...Loe edasi...
This uses MATLAB® for data analysis and statistics, offering a broad review of computational data analysis, in particular algebra, trigonometry, regression modeling, correlation, and graphical representation of results, covering both basic and more...Loe edasi...
In this book, readers embark on an in-depth journey into conducting complex survey analysis with the {srvyr} package and tidyverse family of functions from the R programming language. Additionally, this book teaches readers how to interpret and comm...Loe edasi...
Kiran Sood, Prateek Kalia, Simon Grima, Aryan Chaudhary
(Ilmumisaeg: 01-Nov-2024, Kirjastus: Apple Academic Press Inc., ISBN-13: 9781032713366)
Discusses digital analytics as a new trend using new technologies to measure, collect, analyze, and report on data about learners and their contexts to understand and optimize learning and learning environments....Loe edasi...
This book is designed for students taking basic and advanced courses in statistics, taking an integrative and practical approach to learning statistics. It guides students through navigating SPSS outputs and writing quantitatively, dealing with tech...Loe edasi...
Data Science: A First Introduction with Python focuses on using the Python programming language in Jupyter notebooks to perform data manipulation and cleaning, create effective visualizations, and extract insights from data using classification, reg...Loe edasi...
The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. Modern Statistics with R introduces you to key parts of this modern statistical toolkit....Loe edasi...
Analyzing Baseball Data with R Third Edition introduces R to sabermetricians, baseball enthusiasts, and students interested in exploring the richness of baseball data. It equips you with the necessary skills and software tools to perform all the ana...Loe edasi...
This book is an introductory guide to programming and coding in Stata. Commonly encountered code in the field of medical statistics as well as the analyses of observational data are presented.This book covers loops and macros and then describes othe...Loe edasi...
Empowers you to harness the potential of spatial analysis in addressing pressing geological challenges. Can also be used as a textbook either in introductory courses in spatial analysis or in advanced GIS and Digital mapping - comprehensive guide ta...Loe edasi...
This book is the second in a two-volume series that introduces the field of spatial data science. It moves beyond pure data exploration to the organization of observations into meaningful groups, i.e., spatial clustering. This constitutes a major as...Loe edasi...
In the era of Big Data, distributional data is becoming more prevalent. This book presents a synthesis of research in this area over the last twenty years. It has been carefully edited to ensure it is consistent with respect to style, level, notat...Loe edasi...
This book is the first in a two-volume series that introduces the field of spatial data science. It offers an accessible overview of the methodology of exploratory spatial data analysis. It also constitutes the definitive users guide for the widely...Loe edasi...
Ways that raw and summary data can be turned into visualizations that convey meaningful insights: basic graphs, bar charts, scatter plots, and line charts, and progresses to tree maps, alluvial plots, radar charts, mosaic plots, grouped dot plots, e...Loe edasi...
Foundations of Data Science with Python introduces readers to the fundamentals of data science, including data manipulation and visualization, probability, statistics, and dimensionality reduction. Intended for engineers and scientists, it can be us...Loe edasi...
Data Science for Sensory and Consumer Scientists is a comprehensive textbook that provides a practical guide to using data science in the field of sensory and consumer science through real-world applications.This book is the ideal guide to using dat...Loe edasi...
