Auto Price Estimator

In spring 2023 I was actively getting on top of data and ML from an enigneering POV. To do so I took on the entire curriculum of the ML/AI engineer learning path of codecademy.

(See: codecademy/ml-ai-eng)

To finish the course, I was to design a ML pipeline as a project. This meant finding a fitting subject, finding data, analyzing that data, creating and optimizing a model for it. In addition, this was all to be migrated into a pipeline, where all these steps were included.

The topic became estimating car prices, since it is pretty simple. I felt it was a good topic for doing all the parts without requiring any in-depth domain knowledge. In hindsight I overlooked some things and made some unfactual statements about the data, probably causing the prediction accuracy to drop, but in the end I had a pipeline.

Did it end up being a very good solution to the problem at hand? In hindsight, No (Although useable and semi-accurate)

Did I create everything I set out to make at the beginning by utilizing the knowledge I had gained? Yes.

Read more about the project in the -> GitHub repository <-