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The main goal here is to apply some Supervised Machine Learning classifiers on the Spambase dataset from the UCI Machine Learning Repository and perform Significance analysis afterwards.

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Spam_prediction

The main task of this project is to apply several Supervised Machine learning classifiers on the Spambase dataset from the UCI Machine Learning Repository and perform Significance tests thereafter.

House_Prices_Predictions

Description:-

My second assignment for the Machine Learning course - DV2542. The main task is to compare various Supervised Machine Learning classifiers on the Spambase dataset from the UCI Machine Learning Repository and perform Significance tests thereafter.

The dataset is collected from the UCI Machine Learning Repository. Link:- https://archive.ics.uci.edu/ml/machine-learning-databases/spambase/

Pre-requisites:-

Numpy(1.13.3), Pandas(0.21.0), SciKit-learn(0.19.0).

Installation:-

To install a pre-requisite, use:- pip install <package_name>.

License:-

This project is licensed under the MIT License - see the LICENSE.md file for details.

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The main goal here is to apply some Supervised Machine Learning classifiers on the Spambase dataset from the UCI Machine Learning Repository and perform Significance analysis afterwards.

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