Musical Instruments Image Classification

[aaradhyasinghgaur]

Approach I'd take :- 1. Utilizing 5 models such as DenseNet121 , Xception, VGG16, ResNet50, and InceptionV3 for image classification.
2. Applying data augmentation (rotation, zooming, flipping, shearing, brightness) to enhance dataset robustness.
3. Comparing model performance using accuracy scores, loss/accuracy graphs, and confusion matrices.
4. Conducting EDA for dataset insights, including image distribution, quality, class imbalances, and sample visualization.
5. Documening the process in a comprehensive README file.

Dataset I'll use :- https://www.kaggle.com/datasets/gpiosenka/musical-instruments-image-classification/data

@Niketkumardheeryan @invigorzz313 kindly assign this issue to me.

[invigorzz313]

This issue has been assigned.
Do follow the project guidelines for the PR.
Create a new branch for the PR and avoid committing directly from 'master'.