https://github.com/kaustubhgupta/technocolab-final-project
Final project made during my internship in Technocolabs.
https://github.com/kaustubhgupta/technocolab-final-project
css flask html numpy pandas project python seaborn sklearn
Last synced: about 1 year ago
JSON representation
Final project made during my internship in Technocolabs.
- Host: GitHub
- URL: https://github.com/kaustubhgupta/technocolab-final-project
- Owner: kaustubhgupta
- Created: 2020-08-25T07:55:18.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2021-10-05T09:33:18.000Z (almost 5 years ago)
- Last Synced: 2025-04-12T09:43:29.449Z (about 1 year ago)
- Topics: css, flask, html, numpy, pandas, project, python, seaborn, sklearn
- Language: Jupyter Notebook
- Homepage: http://music-genre-predict.herokuapp.com/
- Size: 2.08 MB
- Stars: 8
- Watchers: 1
- Forks: 6
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Technocolab-Final-Project 😀

## About 😁
This is the final project made during my internship in Technocolabs. In this project, we were given two files, a CSV file containing data about music track title, composer, label, and many other features including track genre. The JSON file consists of technical details about a soundtrack including valence and danceability.
We were given the task to build a classifier for this dataset which was highly unbalanced and then deploying that model to any of the cloud services.
## Link to deployed website ⚡
Sure, here you go: [Music Genre Predict](http://music-genre-predict.herokuapp.com/)
## Preview 📺

## Tech Stack 🏟
- Python (Langauge)
- Libraries:
- Numpy (Data Manipulation)
- Pandas (Data Manipulation)
- Seaborn (Data Visualization)
- Sklearn (Model Building)
- Flask (Model Deployment)
- HTML (Web interface)
- CSS (Web enhancement)
- Heroku (Website Deployment)