Bird Species Classification using Deep Learning

[IkkiOcean]

Pull Request Title: Add Deep Learning Models for Bird Species Classification

Description:

Closes: #40 introduces several deep learning models for the classification of bird species using the dataset available at Kaggle - 200 Bird Species. The dataset consists of 200 species of birds and contains a total of 11,788 images.

Models Implemented:

The following state-of-the-art deep learning architectures have been employed for this task:

•	InceptionResNetV2
•	EfficientNetB0
•	InceptionV3
•	VGG16

Approach:

Each of these models has been fine-tuned on the dataset for optimal performance in classifying the bird species. Pretrained weights on ImageNet were used as a starting point, followed by further training on the bird species dataset.

How Has This Been Tested? ⚙️

• My code follows the code style of this project.
• My code follows the guidelines of this project.
• I have performed a self-review of my own code.
• I have commented my code, particularly wherever it was hard to understand.
• I have made corresponding changes to the documentation.
• My changes generate no new warnings.
• I have added things that prove my fix is effective or that my feature works.

Programs : GSSOC-extd and hacktoberfest

Please review the code and models. Any feedback or suggestions are appreciated.

[github-actions]

Thank you for submitting your pull request! 🙌 We'll review it as soon as possible. In the meantime, please ensure that your changes align with our CONTRIBUTING.md. If there are any specific instructions or feedback regarding your PR, we'll provide them here. Thanks again for your contribution! 😊

[SaiNivedh26]

PR approved ! @IkkiOcean