This is our final week of lectures. In this weeks class I will try to wrap up the whole data mining process and what it involves in a practical sense. The CRISP-DM lifecyle is good but not complete as it doesn’t discuss what needs to happen with each iteration. I’ll go over this and talk about some of the things you need to watch out for and things you need to do. You can then apply these guidelines in your work projects. I will also look at some advances in Data Mining that cover Adaptive Intelligence Applications and Automated Machine Learning, from a data mining perspective and not from a machine learning perspective. Finally, I’ll look at some future areas for data mining, data science, etc that are coming in the very near future.
Click here to download the notes for this week.
Read this Twitter discussion on 30 best practices for Machine Learning engineering
There are no lab exercises for this week,
Use the time to work your assignment for the module.