Scoutium Talenter Hunting Classification

• Tech Stack: Python, Numpy, Pandas, Scikit-Learn, LGBM, Optuna, Oversampling
• Kaggle URL: Project Link

Predicting which class (average, highlighted) player is according to the points given to the characteristics of the players.

In this project I used the following methods

• I used pandas to understand the data.
• I used seaborn and matplotlib to visualize the data.
• I used sklearn for many operations such as data preprocessing and classification performance criteria.
• I used LightGBM for the classification model.
• I used optuna optimization tool for hyperparameter optimization.
• I used oversampling method for data imbalance.