ML Project 4 Results

I am happy to report that I got 100% on the final project I did in the last 2 weeks for my Machine Learning grad class (which is especially great because that was 30% of my grade for the semester!) and I got some good feedback from the professor:

Very good analysis and you showed great potential to become a good researcher!

1. when you code your categories features, 1 of k coding is a good choice. Did you apply this method to all categories features?

2. Some time, normorlize features will make a huge difference. One way to do this is to comput the z-score for features before you train a model on the data.

3. In terms of machine learning application, your analysis is good. If you try to find a social study expert to collobrate with you, I believe your findings can be published on high impacting journals.

4. In order to publish your work, you will need to do some research to found what have been done in this field.

This is especially encouraging since I want to become a data scientist, so hearing positive feedback like this, even encouraging me to publish after having only taken one semester of Machine Learning, feels great!

So, I will take time this summer to do more research and learning and expand on this project (since it was a rush to complete enough to turn in on time in this class but there’s a lot more I want to do with it), and I will collaborate with some people at the university where I work to further distill the results and see if we can apply them to segment out some potential first-time donors for next fiscal year.

This is fun!