To identify lithologies, geoscientists use subsurface data such as wireline logs and petrophysical data. However, this process is often tedious, repetitive, and time-consuming. This project aims to use machine learning techniques to predict lithology from petrophysical logs, which are direct indicators of lithology.

End-to-end project to predict basketball player points. (regression problem)

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Augmentation based on position applied to CRF and XGBOOST algorithms applied to african languages for POS task

Proyecto de predicción de ventas para las proximas 6 semanas de todas las tiendas , con representación de datos, usando Python con librerías distintas como Pandas, Numpy,Matlab, Seaborn para análisis de datos, recopilación e interpretación de los datos, además de modelos predictivos.

XGBoost vasitəsilə neftin gələcək qiymətinin proqnozlaşdırılması layihəsi