Ironhack's Kaggle competition
The repository describes the steps followed in the Kaggle competition about diamonds price prediction, launched by Ironhack as project for the third module, involving Machine Learning.
On the notebook attached you can find the steps I took while taking part of this competition. I decided to use Decision Tree Classifier in order to attach a tag to each diamond, not having in count price (since is the feature to be predicted).
After that, I used Light Gradient Boost Machine (LGBM), focussed on regression in order to infer the price.
The model results after cross validation is around 530.3 RMSE