🚀 Achieved 75.52% accuracy in image classification through a comprehensive project. Employed Convolutional Neural Networks, data augmentation, dimensionality reduction, and Support Vector Machine classification. 🧠 Leveraged CNNs for intricate feature learning. 🌟 Enhanced robustness with data augmentation. 🔍 Optimized efficiency via dimensionality reduction. 📈 Combined SVM for versatile classification.