Andere Kunden interessierten sich auch für
![Data Science]( "Data Science")
Data Science40,99 €![Essentials of Big Data and Analytics]( "Essentials of Big Data and Analytics")
Essentials of Big Data and Analytics40,99 €![Hands-On Data Science with Anaconda]( "Hands-On Data Science with Anaconda")
Hands-On Data Science with Anaconda41,99 €![Data Mining: Analysis, Algorithms and Applications]( "Data Mining: Analysis, Algorithms and Applications")
Data Mining: Analysis, Algorithms and Applications150,99 €![Standard Distributions in Texture Analysis, Volume 3, Standard Distributions in Texture Analysis Volume 3]( "Standard Distributions in Texture Analysis, Volume 3, Standard Distributions in Texture Analysis Volume 3")
Standard Distributions in Texture Analysis, Volume 3, Standard Distributions in Texture Analysis Volume 391,99 €![Business Analysis, Requirements, and Project Management]( "Business Analysis, Requirements, and Project Management")
Business Analysis, Requirements, and Project Management187,99 €![Managing Data Science]( "Managing Data Science")
Managing Data Science34,99 €
Welcome to "Beginning Data Science in R: Data Analysis, Visualization, and Modeling." In this book, we embark on an exciting journey into the world of data science using the R programming language. Whether you're a novice seeking to explore the fundamentals or an experienced practitioner looking for a comprehensive reference, this book is designed to be your companion. Data science has become an integral part of decision-making processes across various industries. From understanding customer behavior to predicting market trends and making informed business choices, the power of data analysis, visualization, and modeling cannot be overstated. R, with its extensive ecosystem of packages and tools, has emerged as a preferred choice for data scientists due to its versatility and ability to handle complex analytical tasks. Our aim in this book is to provide you with a solid foundation in data science techniques using R. We will guide you through the entire data science workflow, from data acquisition and cleaning to exploratory data analysis, visualization, and building predictive models. Each chapter is carefully crafted to introduce concepts progressively, with hands-on examples and practical exercises to reinforce your understanding.