Learning Data mining with R by Packt Publishing
This is the code repository for Learning Data Mining with R [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
Data mining is a growing demand on the market as the world is generating data at an increasing pace. R is one of the most popular programming languages for statistical analysis.
This course will get you up and running with the mathematical basics quickly, which you can directly apply based on what you’ve learned in R. This course covers each and every aspect of data mining in order to prepare you for real-world problems. You'll come to understand the different disciplines in data mining and then delve into a variety of algorithms based on each discipline. At least one of the various classes of algorithms will be covered to broaden your knowledge to dive deeper into the different flavors of these algorithms.
After completing this course, you will be able to solve real-world data mining problems.
- Get to know the basic concepts of R: the data frame and data manipulation
- Discover the powerful tools at hand for data preparation and data cleansing
- Visually find patterns in data
- Work with complex data sets and understand how to process data sets
- Explore graphs and the statistical measure in graphs
- Gain insights into the different association types
- Delve into various algorithms for classification such as KNN and see how they are applied in R
- Evaluate k-Means, Connectivity, Distribution, and Density-based clustering
- Grasp how to use deep neural Decide what algorithms actually should be used and what the desired and possible outcomes of the analysis should benetworks to build an optical character recognition system
This video appeals to anyone who works with a lot of data and wants to make sense of this data in the most efficient manner. The video will appeal to aspiring data scientists, data analysts, and anyone who wishes to perform advanced analytics in future.Basic familiarity with R programming is expected..: