Musical Instruments Image Classification

[aaradhyasinghgaur]

Closes :- #787 Approach I took :- 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.

I have worked on this issue..kindly review my pr and in case of no problems merge it with suitable lable (Level-3) if possible as I have tarined the entire set on 5 different models with excellent accuracy.