Animal Image Classification

My Contribution

• Downloaded and prepared the animal image dataset from Kaggle.
• Configured the image preprocessing and augmentation pipeline using Keras ImageDataGenerator.
• Prepared the three-class classification task for Tigers, Dogs, and Cats.
• Designed and implemented a CNN architecture with Conv2D, MaxPooling, Dropout, and Dense layers.
• Configured the Adam optimizer, L2 regularization, and EarlyStopping to improve training stability and reduce overfitting.
• Trained the deep learning model using TensorFlow and Keras.
• Evaluated model performance using accuracy, loss, classification results, and a confusion matrix.
• Created visualizations for training and validation accuracy and loss.
• Prepared the trained model for use in a Streamlit dashboard for animal image classification.