Beat Overfitting in Kaggle Competitions - Proven Techniques


Ready to take your Kaggle competition game to the next level? Learn how to recognize and prevent overfitting for top-notch results.

Continue reading

Kaggle Evaluation Metrics Used for Regression Problems


"This post describe evaluation metrics used in Kaggle competitions where problem to solve is has regression nature. Eight different metrics are described, namely - Absolute Error (AE), Mean Absolute Error (MAE), Weighted Mean Absolute Error (WMAE), Pearson Correlation Coefficient, Spearman\u2019s Rank Correlation, Root Mean Squared Error (RMSE), Root Mean Squared Logarithmic Error (RMSLE), Mean Columnwise Root Mean Squared Error (MCRMSE)."

Continue reading

What's Cooking


Exploratory Data Analysis of the Kaggle's "What's cooking" competition dataset to get understanding what kind of data we are dealing with and get intuition of existing dependencies.

Continue reading