This Jupyter Notebook explores the SMS Spam dataset obtained from UCI Machine Learning repository. The notebook also compares performance of few machine learning models in their ability to analyze text data.
Using a virtual environment is highly recommended. Once your virtual environment is ready, clone the repository into your virtual environment.
git clone https://github.com/aliasm2k/sms-spam.git .
Once the repository is cloned, install the required dependencies by executing the following command from the terminal.
pip install -r requirements.text
Launch the Jupyter Notebook web interface by executing the following command from the terminal.
jupyter notebook
MIT License
Copyright (c) 2017 Karthik Narendran
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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