This is the code repository for Advanced Data Mining projects with R [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
Advanced Data Mining Projects with R takes you one step ahead in understanding the most complex data mining algorithms and implementing them in the popular R language. Follow up to our course Data Mining Projects in R, this course will teach you how to build your own recommendation engine. You will also implement dimensionality reduction and use it to build a real-world project. Going ahead, you will be introduced to the concept of neural networks and learn how to apply them for predictions, classifications, and forecasting. Finally, you will implement ggplot2, plotly and aspects of geomapping to create your own data visualization projects.By the end of this course, you will be well-versed with all the advanced data mining techniques and how to implement them using R, in any real-world scenario.
- Create predictive models in order to build a recommendation engine
- Implement various dimension reduction techniques to handle large datasets
- Acquire knowledge about the neural network concept drawn from computer science and its applications in data mining
To fully benefit from the coverage included in this course, you will need:
Data analysts and data scientists with some knowledge of R, who need a helping hand in developing complex data mining projects are the ideal audience for this video course. They should have prior knowledge of basic statistics and some experience with the basic data mining techniques and algorithms.
This course has the following software requirements:
RStudio