Dog_Vs_cat CLassification added

[Shy029]

Proposed Changes

• Implemented Dogs vs. Cats Classification using Transfer Learning with MobileNetV2 from TensorFlow Hub.
• Integrated Kaggle API to access the large dataset directly without local downloads.
• Resolved the import issue with tf.keras.Sequential by providing instructions to install and use tf_keras.Sequential.
• Achieved Test Accuracy of 99% with optimized loss of 0.0445.

---

Additional Info

• How to Use Kaggle API:

  1. Create a Kaggle account and verify via email or phone.
  2. Generate a new API token from Account Settings (downloads kaggle.json file).
  3. Upload kaggle.json to Google Colab to access the dataset directly.

• Dataset Used:

  • Dogs vs. Cats Dataset from Kaggle.
  • Note: Due to the dataset's large size, we recommend using the Kaggle API instead of manual download.

• Common Errors Resolved:

  • Compatibility issue with TensorFlow’s default Keras module. Solution:

    pip install tf_keras

    Replace:

    model = tf.keras.Sequential([...])

    With:

    import tf_keras
    model = tf_keras.Sequential([...])

---

Results

• Test Loss: 0.0445
• Test Accuracy: 99.00%

[github-actions]

👋 Thank you for opening this pull request! We appreciate your contribution to improving this project. Your PR is under review, and we'll get back to you shortly.
Don't forget to mention the issue you solved!.

To help move the process along, please tag @UppuluriKalyani, @Neilblaze, and @SaiNivedh26 for a faster review!

[github-actions]

🎉🎉 Thank you for your contribution! Your PR #424 has been merged! 🎉🎉