Imagine being able to predict how well a student will perform in a course based on their past grades, attendance, and other factors. Sounds like a superpower, right? Well, that’s exactly what I built as my first project in Python using Numpy and Scikit-learn – a student performance predictor.
What’s fascinating is that I implemented the gradient descent algorithm from scratch to better understand how it works. Now, I’m eager to hear your thoughts – is it good? Does it need improvements? You can check it out on GitHub, where I’ve also included an explanatory PDF to give you a deeper dive into the project.
I’m excited to hear your feedback and see how this project can be taken to the next level. Who knows, maybe one day we’ll be able to use machine learning to create a more personalized and effective learning experience for students.