The Statistics and Machine Learning with R Workshop is a comprehensive resource packed with insights into statistics and machine learning, along with a deep dive into R libraries. The learning experience is further enhanced by practical examples and hands-on exercises that provide explanations of key concepts.
Starting with the fundamentals, you’ll explore the complete model development process, covering everything from data pre-processing to model development. In addition to machine learning, you’ll also delve into R's statistical capabilities, learning to manipulate various data types and tackle complex mathematical challenges from algebra and calculus to probability and Bayesian statistics. You’ll discover linear regression techniques and more advanced statistical methodologies to hone your skills and advance your career.
By the end of this book, you'll have a robust foundational understanding of statistics and machine learning. You’ll also be proficient in using R's extensive libraries for tasks such as data processing and model training and be well-equipped to leverage the full potential of R in your future projects.
publication date
2023-10-25
what you will learn
Hone your skills in different probability distributions and hypothesis testing
Explore the fundamentals of linear algebra and calculus
Master crucial statistics and machine learning concepts in theory and practice
Discover essential data processing and visualization techniques
Engage in interactive data analysis using R
Use R to perform statistical modeling, including Bayesian and linear regression
key features
Advance your ML career with the help of detailed explanations, intuitive illustrations, and code examples * Gain practical insights into the real-world applications of statistics and machine learning * Explore the technicalities of statistics and machine learning for effective data presentation * Purchase of the print or Kindle book includes a free PDF eBook
approach
Starting from foundational concepts, you’ll apply your learning through detailed guided exercises in each chapter. You’ll go from common data manipulation and processing techniques, to data transformation, to the fundamentals of linear algebra and calculus in R. Finally, the fundamental topics of mathematical statistics in R will include sampling, linear regression, and Bayesian statistics.
audience
This book is for beginner to intermediate-level data scientists, undergraduate to masters-level students, and early to mid-senior data scientists or analysts looking to expand their knowledge of machine learning by exploring various R libraries. Basic knowledge of linear algebra and data modeling is a must.
short description
The book is a foundational guide for developers keen on mastering machine learning and statistical modeling in R. It offers a hands-on approach along with real-world applications. Whether you're a beginner or looking to upgrade your skills, the book equips you with practical knowledge to tackle a wide array of tasks in ML and statistics.
subtitle
Unlock the power of efficient data science modeling with this hands-on guide
keywords
Discovering statistics using r, Discovering statistics, Mathematical statistics, An introduction to statistical learning, Bayesian statistics
Product ISBN
9781803240305
