Kaggle PlayGround series competitions
Sabyasachi Chakrabarty
Kaggle-Sep-TPS-2024
ANOVA testing to target variable to perform target encoding saving feature space
data normalisation, correlation
comparing models (linear regression, XGBoost, Random Forest Regressor, LGBM regressor)
Kaggle-Jan-TPS-2022
Explored PCA
Algorithms explored and compared are Random Forest, LGBM
Comapred Grid search and Random search
Kaggle-Aug-TPS-2021
Detailed exploration of the data set and Model
Outlier detection and its visualisation
Feature exploration
Manual hyperparameter tuning to understand the effects of the parameters on the model
Explored Random Forest; PCA; LGBM.
Kaggle-July-TPS-2021
First ever competition on Kaggle, an to competitions, a time series analysis for
Time Analysis and Regression analysis
AR/MA time model
ARIMA / SARIMA model wiht various orders
Accuracy with Mean Absolute Percentage Error(MAPE)
Robust Scaling (Outliers)
Ridge Regression (Multicollinearity)
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Posted Sep 25, 2024
Exploring and analysing diverse data science challenges, performing EDA, machine learning and deep learning.
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