Data-Science-Playground

Introductory code snippets which deals with the basics of data science and machine learning which you can rely on anytime

Key

1. contains basic and important functions of pandas and numpy.
2. contains introductory snippets for graph libraries like matplotlib and seaborn.
3. contains how data is generated using dynamically using sklearn and it's functions.
4. contains code snippets that helps us to train and test the data using linear regression model.
5. contains code snippets that helps us to train and test the data using logistic regression model.
6. contains code snippets that helps us to train and test the data using decision tree and the tree is drawn using graphviz.
7. contains code snippets that helps us to build the perceptron model from scratch and helps us train and test the data using perceptron model of sklearn.
8. contains code snippets that helps us to deal with the imbalance in the dataset.
9. contains code snippets that helps us to train and test the data using SVM model with different kernels.
10. contains code snippets that helps us to build the KNN and weighted KNN model from scratch and helps us train and test the data using KNN and weighted KNN model of sklearn.
11. contains code snippets that helps us to perform ensemble and stacking (Unsupervised).
12. contains code snippets that helps us to build the kmeans and kmodes model from scratch and helps us train and test the data using kmeans, kmodes model of sklearn (Unsupervised).

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Further improvements are always welcome.

- Fork the repository
- make changes
- create pull request

Happy contributing