Get suggestions on genre of music you may like based off of your age and gender. Built using Decision Tree Algorithm from scikit-learn machine learning library for Python Programming Language.
Start by either downloading the zip file or clone with HTTPS.
- Anaconda Distribution (https://www.anaconda.com/distribution/)
- Python 3.7.3 (https://www.python.org/downloads/)
git clone https://github.com/VasuGoel/music-recommender.git
- After installing the Python 3.7.3 and the Anaconda Distribution of python, open the terminal, and type
jupyter notebook
- You'll be redirected to a localhost server in your web browser running the Jupyter Notebook Dashboard at http://localhost:8888/tree
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Locate the repository from the Jupyter Notebook dashboard and click the music-recommender.ipynb file in the project root
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Click the cell containing the code and click run
- [Pandas] (https://pandas.pydata.org/pandas-docs/stable/) - Python library that offers data structures and operations for manipulating numerical tables and time series.
- [Scikit-Learn] (https://scikit-learn.org/) - Scikit-learn is a free software machine learning library for the Python programming language
- [Joblib] (https://github.com/joblib/joblib) - Joblib is a set of tools to provide lightweight pipelining in Python.
- [DOT] (https://www.graphviz.org/) - DOT files are used to create multiple documents that have similar formatting, such as company letterheads, business memos, or envelopes
- [Python] (https://www.python.org/) - Python is an interpreted, high-level, general-purpose programming language.
- [Jupyter Notebook] (https://jupyter.org) - The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.
- Vasu Goel (https://github.com/VasuGoel)
This project is licensed under the MIT License - see the LICENSE file for details