A lightweight and efficient computer vision solution for classifying various fruits using MobileNetV2 and transfer learning. Includes robust data preprocessing pipelines, clear repository structure, and detailed documentation for easy collaboration.

I developed a simple neural network using TensorFlow and Keras to classify Iris species based on their features. This project serves as a foundational step in understanding neural networks and their application in classification tasks.

Convolutional Neural Network (CNN) for classifying images from the CIFAR-10 dataset.

Image classification project to detect defective products in manufacturing processes using deep learning. Helps automate quality control by classifying items as 'Defective' or 'Non-Defective'.

Developed a deep learning model to accurately classify handwritten digits from the MNIST dataset.