Linear regression exploration

Inspiration

I learned some of the foundations of machine learning over the summer and wanted a chance at implementing some things I learned. Plus, as someone wanting to get into the AI/Machine Learning field, I felt like this was a good opportunity

What it does

It utilizes features from an online dataset pertaining to students such as their grades, study time, etc in order to approximate what their final grade would be

How we built it

I used Google Colab as my IDE and first implemented the built-in SciKit linear regression. I then wrote code for manual linear regression followed by using neural networks as well.

Challenges we ran into

In my manual linear regression portion, I had some trouble implementing the logic and working with types.

Accomplishments that we're proud of

Getting my code and logic to work properly and having my project actually make good approximations

What we learned

How to set up and implement manual linear regression and neural networks

What's next for Linear regression exploration

Beyond linear regression, learning how to implement logistic regression and reinforcement learning alongside understanding the machine learning behind LLMs

Built With

• python