Get to grips with key data visualization and predictive analytic skills using R
About This Book
• Acquire predictive analytic skills using various tools of R
• Make predictions about future events by discovering valuable information from data using R
• Comprehensible guidelines that focus on predictive model design with real-world data
Who This Book Is For
If you are a statistician, chief information officer, data scientist, ML engineer, ML practitioner, quantitative analyst, and student of machine learning, this is the book for you. You should have basic knowledge of the use of R. Readers without previous experience of programming in R will also be able to use the tools in the book.
What You Will Learn
• Customize R by installing and loading new packages
• Explore the structure of data using clustering algorithms
• Turn unstructured text into ordered data, and acquire knowledge from the data
• Classify your observations using Naïve Bayes, k-NN, and decision trees
• Reduce the dimensionality of your data using principal component analysis
• Discover association rules using Apriori
• Understand how statistical distributions can help retrieve information from data using correlations, linear regression, and multilevel regression
• Use PMML to deploy the models generated in R
In Detail
R is statistical software that is used for data analysis. There are two main types of learning from data: unsupervised learning, where the structure of data is extracted automatically