Music Genre Classification System Part-13 | Building Web Application using Streamlit

Hello and Welcome guys,
In this project, we'll learn how to make a powerful deep-learning model for 10 different classes of music audio.
In this video, we'll build a web application for a music genre prediction system using Streamlit.
We'll use our music genre prediction model which we created earlier to build a web application.
Also, we will see things in detail how we can make rapid UI of web applications and integrate our machine learning/deep learning model into it

In the next video of this playlist, we will make a music genre prediction web application
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00:00 - Recap
00:18 - Web Application
04:00 - Implementation

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#imageclassification #convolutionalneuralnetworks #audioclassification
#deeplearning #datascienceprojects #machinelearning #musicgenre #featureengineering #audiofeatureextraction #tensorflow #sklearn #modeltraining #modelevaluation #accuracy #datavisualization #matplotlib
#confusionmatrix #precision #recall #f1score #streamlit #webapp #webapplicationdevelopment
Playlist Link: https://www.youtube.com/playlist?list=PLvz5lCwTgdXCd200WNDupTMo15DP9iryv

Project Link: https://github.com/animesh1012/machineLearning/tree/main/Music_Genre_Classification

Trained Model file (h5/keras) :
https://drive.google.com/drive/folders/19rydvWDYCJWIEjpMRf-nLbzEogi0h8qx?usp=sharing

Dataset Link:
https://www.kaggle.com/datasets/andradaolteanu/gtzan-dataset-music-genre-classification/data

Видео Music Genre Classification System Part-13 | Building Web Application using Streamlit канала SPOTLESS TECH