ISBN:
9781835082539
,
183508253X
Language:
English
Pages:
1 online resource (1 video file (22 hr., 25 min.))
,
sound, color.
Edition:
[First edition].
DDC:
519.50285/5133
Keywords:
R (Computer program language)
;
Computer programming
;
Machine learning
;
Instructional films
;
Nonfiction films
;
Internet videos
Abstract:
R is a programming language and environment designed for statistical computing, data analysis, and graphical representation. R is widely used by statisticians, data scientists, researchers, and analysts for various tasks related to data manipulation, statistical modeling, and visualization. R is particularly well-suited for tasks involving data analysis, visualization, and statistics, chosen for its flexibility and a wide array of available tools. This course takes us on a transformative journey through R programming, from foundational concepts to cutting-edge techniques. We delve into R's fundamentals, data types, variables, and structures. We will explore R programming with custom functions, control structures, and data manipulation. We will analyze data visualization with leading packages, statistical analysis, hypothesis testing, and regression modeling. With regular expressions, we will understand advanced data manipulation, outlier handling, missing data strategies, and text manipulation. We will learn about ML with regression, classification, and clustering algorithms. We will explore DL, neural networks, image classification, and semantic segmentation. Upon completion, we will create dynamic web apps with Shiny and emerge as skilled R practitioners, ready to tackle challenges and contribute to data-driven decision-making. What You Will Learn Excel in R basics and advanced data science techniques Transform, visualize, and aggregate data with precision Craft compelling visuals using ggplot, Plotly, and leaflet Implement regression, classification, and clustering models Explore neural networks, image classification, and segmentation Develop dynamic web apps using R Shiny for engaging user experiences Audience The course caters to aspiring and established data scientists, analysts, programmers, researchers, and professionals seeking to enhance their skills in data manipulation, statistical analysis, ML, and DL using R programming. It caters to individuals with varying experience levels, from beginners looking to enter the field to experienced practitioners aiming to expand their expertise in data-driven decision-making and advanced analytics. Prerequisites include prior programming experience but this course can accommodate learners with varying levels of data science concepts and R programming familiarity. About The Author Bert Gollnick: Bert Gollnick is a proficient data scientist with substantial domain knowledge in renewable energies, particularly wind energy. With a rich background in aeronautics and economics, Bert brings a unique perspective to the field. Currently, Bert holds a significant role at a leading wind turbine manufacturer, leveraging his expertise to contribute to innovative solutions. For several years, Bert has been a dedicated instructor, offering comprehensive training in data science and machine learning using R and Python. The core interests of Bert lie at the crossroads of machine learning and data science, reflecting a commitment to advancing these disciplines.
Note:
"Updated in September 2023.". - Online resource; title from title details screen (O'Reilly, viewed October 11, 2023)
