This repo consists of different Kaggle Data Science challenges I've solved.
All of them have been implemented in Python on Jupyter.
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A couple Kaggle Data Science challenges solved using Exploratory Data Analysis (EDA), followed by feature selection, data imputation, class imbalancing techniques & finally experimenting with different ML algorithms like GBMs, Random Forest, Kernel SVMs, etc.
vikram71198/ML_Case_Study
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A couple Kaggle Data Science challenges solved using Exploratory Data Analysis (EDA), followed by feature selection, data imputation, class imbalancing techniques & finally experimenting with different ML algorithms like GBMs, Random Forest, Kernel SVMs, etc.
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