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Machine learning made easy with BlueSky Statistics
25 May 2017 @ 1:00 pm - 2:00 pm
Please join this free educational event in which we will be discussing the application of machine learning techniques and demonstrating how to easily build a random forest model using BlueSky Statistics. Random Forests are one of the most popular machine learning procedures and can be used to develop highly accurate predictions that estimate everything from campaign response to satisfaction and customer churn. To demonstrate the power of machine learning we’ll be using BlueSky Statistics, a new easy-to-use analytical tool based on the open source statistical language R.
The Random Forest technique is an extremely versatile machine learning method which offers the ability to perform both regression and classification tasks, so can be used to address a wide range of predictive problems, from simple classification problems such as whether someone will respond to a campaign or not, to more complex regression problems such as predicting how much a customer is likely to spend with you as a result of that campaign.
During this event you will learn
- A brief overview of machine learning and where the random forest technique fits
- What random forest models are and why they’re so powerful
- How to build a random forest model using the open source statistical language R
- Addressing different types of predictive problems with the random forest technique