I would like to build a linear regression machine learning model, which, taking in a student’s age, attendance, hours studied, hours slept, and exam difficulty, gives a predicted exam score.
I finished creating and refining my AI model.
I
-> normalised my data
-> added more features
My MAE decreased to 8.3, which I’m happy with for now.
I will save the model with pickle and start working on my backend next.
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nice! this AI stuff is pretty tough… glad you figured it out!
I:
-> finished importing all required models
-> generated a correlation matrix
-> used online tutorials and ChatGPT to learn how to train and evaluate a model
-> trained and evaluated my model
But the MAE is quite high, at an average of 9 points off when I’d like it to be more precise. I will need to find a way to improve my model.
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I:
-> finished planning my project, finalising how I’m going to make it step-by-step
-> found and cleaned up data for my project
-> started installing necessary libraries for my project.
I’ve run into some issues I hope to fix later.
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I continued planning my project.
I finalised:
-> what it will do (predict exam scores and give tips to help students based on their input)
-> what technologies it will use (Python/Flask, HTML/CSS, scikit-learn, etc.)
-> it’s structure
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I started planning my project.
This involved defining my prior knowledge and interests to hone in on a specific goal – what do I actually want it to do? What am I able to do? What do I want to create?
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