https://github.com/anushadatta/neural-networks-deep-learning

🔗 Music Genre Classification & HDB Price Prediction.
https://github.com/anushadatta/neural-networks-deep-learning

keras neural-networks tensorflow

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🔗 Music Genre Classification & HDB Price Prediction.

• Host: GitHub
• URL: https://github.com/anushadatta/neural-networks-deep-learning
• Owner: anushadatta
• Created: 2021-12-29T09:34:33.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2022-01-08T17:59:48.000Z (about 3 years ago)
• Last Synced: 2024-12-11T22:28:24.403Z (2 months ago)
• Topics: keras, neural-networks, tensorflow
• Language: Jupyter Notebook
• Homepage:
• Size: 4.78 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Neural Networks & Deep Learning

> CZ4042 Neural Networks & Deep Learning \

> School of Computer Science and Engineering \

> Nanyang Technological University

This repository consists of CZ4042 Assignment 1, which is composed of the following problem sets:

## (A) Music Genre Classification

AIM: Perform music genre classification by predicting the genre label for a given audio file.

DATASET: GTZAN dataset

* ```features_30_sec.csv```

* 1000 audio tracks, 30 seconds each

* Audio tracks preprocessed into 57 features

* Genres (10 labels): blues, classical, country, disco, hip-hop, jazz, metal, pop, reggae and rock

* 1 pattern: filename + audio length + 57 features + label/genre

## (B) HDB Price Prediction

AIM: (i) Perform retrospective prediction of HDB housing prices (resale_price), (ii) Identify the most important features that contributed to the prediction (Recursive Feature Elimination)

DATASET: Publicly available data on HDB flat prices in Singapore, obtained from data.gov.sg on 5th August 2021

* ```hdb_price_prediction.csv```

* Original feature set modified with other datasets to add informative features, as outlined in ```Assignment1.pdf```