- Exploring Dataset - info, describe and conclusions from them
- Checking Outliers and Plotting them using seaborn.boxplot
- Calculating Correlation and plotting it using seaborn.heatmap
- Plotting Graphs for Quality vs other features and giving conclusions for each graph
- Plotting and Calculating Skewness and Kurtosis
- Removing Skewness using Interquartile Range(IQR)
- Plotting graphs to Compare Skewness after removing Outliers
- Performing Scaling of Data using StandardScaler
- Preparing Training and Test dataset using StratifiedShuffleSplit
- Linear Regression followed by Hyperparameter tuning using RandomizedSearchCV
- KNN followed by Hyperparameter tuning using RandomizedSearchCV
- Random Forest Classifier followed by Hyperparameter Tuning using RandomizedSearchCv
- Plotting graph of Models vs Cross Validation Score
- Plotting graph of Models vs Accuracy on Test Data
The dataset used can be downloaded here (Kaggle) - Click to Download
Feel free to mail me for any doubts/query :email: [email protected]
Made with ❤️ by Sahil Chachra
MIT © Sahil Chachra