This repository contains various material in support of the RapidMiner overview talk planned to be given to the Reading Data Science group in March 2019.
RapidMiner is an extremely powerful and easy to use environment for data science. The clue is in the name: RapidMiner. It really is the work of a few minutes to rapidly create a machine learning model without having to write any software. Of course, there is a learning curve, and this talk will give a basic introduction and overview based on an expert's view but aimed at beginners. The intention is to help get you up the learning curve more quickly, make a first model, and help you decide if you could use RapidMiner in your day-to-day work.
We will cover
- Installation of RapidMiner Studio: Community Edition
- GUI features
- Creating a prediction process
- Changing things
- Where to go next
At the end of the talk, attendees will have enough information to help them decide if RapidMiner is for them and to allow them to continue to use it.
The processes and content shown in the talk are stored in this repository. The file RapidMinerOverview.html contains the slides and these are also contained in the file RapidMinerOverview.zip.
I am a data scientist and part time lecturer. Day to day, I use R, Python, and, of course, RapidMiner. I have been using RapidMiner for nearly 10 years, I am a certified RapidMiner Master, and I have created on-line RapidMiner training material. I have also authored and edited books about RapidMiner and Data Mining in general.