Advanced Data Mining projects with R
- 1.5 hours on-demand video
- 1 downloadable resource
- Full lifetime access
- Access on mobile and TV
- Certificate of Completion
Get your team access to 4,000+ top Udemy courses anytime, anywhere.Try Udemy for Business
- 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
Recommendation is a technique by which the algorithm detects what the user is buying. You would always like to be recommended things similar to your interest or things you have bought before. Recommendation engine helps in doing that.
When there are a lot of variables, it becomes difficult to extract data. We need to devise something that will let us gather data in less number of variables. Dimensionality reduction provides you with that solution.
Before working on neural networks, we need to understand the theory behind neural networks.
- They should have prior knowledge of basic statistics and some experience with the basic data mining techniques and algorithms.
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.
About the Authors
Pradeepta Mishra is a data scientist, predictive modeling expert, deep learning and machine learning practitioner, and econometrician. He currently leads the data science and machine learning practice for Ma Foi Analytics, Bangalore, India. Ma Foi Analytics is an advanced analytics provider for Tomorrow's Cognitive Insights Ecology, using a combination of cutting-edge artificial intelligence, a proprietary big data platform, and data science expertise. He holds a patent for enhancing the planogram design for the retail industry. Pradeepta has published and presented research papers at IIM Ahmedabad, India. He is a visiting faculty member at various leading B-schools and regularly gives talks on data science and machine learning.
Pradeepta has spent more than 10 years solving various projects relating to classification, regression, pattern recognition, time series forecasting, and unstructured data analysis using text mining procedures, spanning across domains such as healthcare, insurance, retail and e-commerce, manufacturing, and so on.
If you have any questions, don't hesitate to look him up on Twitter via @mishra1_PK—he will be more than glad to help a fellow web professional wherever, whenever.
- 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.