EasyML is a web-based platform that makes it easier for people to use complex machine learning programs. My final project for Harvard's CS50 (Fall 2021)
As a website built in the CS50 IDE, the code should be compiled there and the server should be created in VS Code. To run the machine learning algorithms, run the attached .ipynb files (titled "petclassifier.ipynb" and "proteinclass.ipynb") on a notebook before using the website. You can also run it on my Deepnote notebook here: https://deepnote.com/project/EasyML-0IwyrG_BREGxLcx3wtQ0dA/%2Fproteinclass.ipynb. The Protein Classifier takes about 15 minutes to run at first, but once it has finished, the web application should run almost instantaneously.
Start the server from the CS50 IDE and from the website's homepage (Home.html), you can see a greeting to the website and three sub-blocks of text.
The first block presents the "Protein Classification" tool. Clicking the hyperlink takes you to the Protein Classification page, which has more details about the model as well as a web app connected to the program. By typing (or more likely, pasting) an amino acid sequence into the text box, the model will tell you what type of protein that sequence codes for.
The second block presents the "Pet Classification" tool. Clicking on that hyperlink takes you to the Pet Classification page, which has information about the model being used and the web app for that classification program. You can upload a photo with a dog or cat in it into the web app, which will be run through the algorithm to classify what animal your pet is.
The third block gives my email to users to receive feedback or questions about the platform, as well as information about the website's future.
The homepage is hyperlinked on all of the pages in the header and in text at the bottom of the pages. The HTML code for the website was based on HTML code provided by nicepage.com. Also, all of the machine learning code is hyperlinked to the original programmers' Kaggle pages, so that you can check out their algorithms.
www.youtube.com/watch?v=h0ewaP9G2Zo
Q: What if the web app says "This app has experienced an error"? A: It is likely that the notebook with the ML algorithms is not running, which means that the uplink server is disconnected. Run the Deepnote code first so that it can be connected to the web app.
Q: How do I go back to the home page? A: Click on the title of the header, which is hyperlinked to the homepage.
Q: Where do I learn more about the source code for the machine learning algorithms or the HTML code that was used for the page? A: All of these websites are cited on the website, either in their respective pages or in the footer of the site.
Q: How do I get in contact with you? A: My email is on the homepage!