Matlab neural networks (laboratory projects).

Transfer learning using InceptionV3 Keras model for Chest X-Ray Classification

Build a Python application that can train an image classifier on a dataset, then predict new images using the trained model.

Capstone Project for Udacity Machine Learning Engineer NanoDegree

A microservice that uses keras and tensorflow to classify images

Flowers classification app using Deep Neural Networks

Image Classifier using common DL Frameworks

Project 2 of Udacity's Introduction to Machine Learning Nanodegree Program

Flowers Image Classifier that can classify 102 different types of flowers from their images using transfer learning.

Utilized CNN models to classify images of mountains and forests, treating mountains as the positive class and forests as the negative class. We compare the performance of a pre-trained model, a custom CNN model, and a CNN model with data augmentation.

Basic image classifier made from scratch using Deep learning techniques.

Udacity's project of classifying images by using pytorch and transfer learning

Built image classification deep learning architectures - AlexNet, VGG16, and ResNet using transfer learning and fine-tuning in PyTorch. Final model accuracies achieved are AlexNet-81.2%, VGGNet-85.6%, ResNet-84.7% on 10K test images.

A deep learning image classifier developed by using the Keras framework and the Fashion-MNIST dataset.

A cat and dog classifier.

An easy-to-use CLI tool for training and testing image classifiers

This is an image classifier using a convolutional neural network (using keras library, tensorflow backend) in which the dependent variable is binary (can be explained by two classes)

A command line application that implements an image classifier with PyTorch. Part 2 of final project for Udacity's AI Programming with Python Nanodegree program.

An iOS application to answer the age old question if something is a sandwich or burger!