- Given dataset of Diamonds with features I have preprocessed data using different libraries such as Pandas, Numpy etc.
- Did Correlation analysis between features.
- Performed feature engineering, feature enconding and scaling.
- Lastly, I've applied different regression models (Linear, Lasso, AdaBoost, Ridge, GradientBoosting, RandomForest, KNN) and compared their predictive accuracy.
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Given dataset of Diamonds with features such as Cut, Carat, Clarity etc. I have used libraries such as Numpy, Pandas, Matplotlib, Seaborn to Analyse and Estimate the Price of Diamonds based on the features. Implemented Algorithms using Scikit-Learn to increase the R2 score.
DChauhan9/Diamonds-Classifications
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Given dataset of Diamonds with features such as Cut, Carat, Clarity etc. I have used libraries such as Numpy, Pandas, Matplotlib, Seaborn to Analyse and Estimate the Price of Diamonds based on the features. Implemented Algorithms using Scikit-Learn to increase the R2 score.
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