Data Science Essentials with R: Learn with focus on data manipulation, visualization, and machine learningКНИГИ » ПРОГРАММИНГ
Название: Data Science Essentials with R: Learn with focus on data manipulation, visualization, and machine learning Автор: Abhishek Das Издательство: BPB Publications Год: 2025 Страниц: 268 Язык: английский Формат: epub (true) Размер: 10.1 MB
This book teaches you to draw insights from your data. In today's data-driven business landscape, making informed decisions requires effective data analysis. This book guides you through the steps to import, structure, and visualize your data in R, and apply statistical and ML algorithms to drive better insights.
This book offers a thorough introduction to data science, starting with R programming basics and advancing to ML and data visualization. Learn to clean, explore, and transform data using tools like dplyr. Key statistical concepts like probability, hypothesis testing, and modeling are covered, providing a foundation for data-driven decisions. Discover supervised and unsupervised ML techniques, feature engineering, and model evaluation. The book also provides career guidance in data science, including skill-building tips and job search strategies, equipping you to excel in this growing field.
The Chapter 2 will briefly give an overview of R language and R studio interfaces. You will learn how to install and load packages and create different types of R objects, such as vectors, matrices, lists, arrays, and data frames. R has an extensive collection of built-in functions. This language also has its own help page, which can be accessed to learn more about the functions. You will understand how to create a function on your own as well. Next, you will learn to load a dataset in R and export any data to your system. This chapter will make you comfortable exploring your data in the next stage.
By the end of this book, you will be able to confidently use R to prepare data for analysis and apply ML algorithms to make predictions and drive business decisions.
Key Features:
- Master R for effective data analysis and ML. - Analyze data, identify patterns, and drive informed decision-making. - Learn by doing hands-on R codes and applying ML techniques.
What you will learn:
- Use R to clean, analyze, and visualize data effectively. - Apply statistical techniques to find patterns and trends in data. - Understand and implement key ML algorithms step-by-step. - Data visualization techniques using ggplot2 to create informative visualizations. - Strong foundation in statistical concepts, including probability theory, hypothesis testing, and statistical modeling.
Who this book is for: This book is ideal for individuals with a basic understanding of programming and statistics who aspire to enter the field of data science. Professionals such as data analysts, software engineers, and researchers will find this book particularly valuable as it provides a practical approach to leveraging data for informed decision-making.
1. The Data Science Landscape 2. R Basics 3. Exploring Data 4. Wrangling Data 5. Working with Dates 6. Manipulating Strings 7. Visualizing Data 8. Feature Engineering 9. Statistics and Probability 10. Introducing ML 11. Training Machine Learning Models 12. Building a Career in Data Science
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Beginning Data Science in R Название: Beginning Data Science in R: Data Analysis, Visualization, and Modelling for the Data Scientist Автор: Thomas Mailund Издательство: Apress...
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Data Science Essentials with R: Learn with focus on data manipulation, visualization, and machine learning 
