Here, you'll find:
- an API-backend written in Flask which makes predictions with a neural network (Keras) that I trained. This model attempts to function as a sentiment analyzer and predict the emotions of text. The frontend functions like how a SPA would, except, admittedly, the design is very basic. Functional-enough to showcase the model in the backend, but basic. I used Javascript and a little JQuery to achieve the SPA-like frontend, where the page does not need to always need to reload to change the page's content. I have included instructions in the README to get this up and running, but let me know if you need any assistance on this!
- an implementation of K-Nearest Neighbors, a machine learning algorithm. The most important file for you to look at would be knn.py. You can get a good sense of my programming-style from it!
- a PHP file/script that pulls the most recent articles from various categories and "HTMLifies" for emailing-purposes (newsletter). I wrote this during my time as the webmaster of my school's online newspaper.