This repo contains the python codes of my final thesis "Analysis of leaf species and detection of diseases using image processing and machine learning methods".

This project uses a pre-trained ResNet50 model from the FastAI library to detect pneumonia in chest X-rays. The dataset which is available on kaggle is used for training the model which classifies the chest xray as NORMAL, VIRAL or BACTERIAL and this project is deployed on Flask

COVID-19-Xray-Dataset Deep Learning using 3 models

Classifying MonkeyPox Images using various Deep Learning networks (VGG16,VGG19,RESNET50 and a Custom CNN model)

A supermarket chain called Good Seed wanted to see if Data Science could help them comply with the law by ensuring that they did not sell age-restricted products to underage customers. My task was to build and evaluate a model to verify a person's age.

Project for the University Master Degree Course of Statistical Methods for Machine Learning.

Classifying Pneumonia images and normal lung images using RESNET50 and Customized CNN models.

A predictive analytics in Fishery using Deep learning techniques. It includes classifying what type of fish it is and also the disease it is affected with.

Cette application utilise l'apprentissage automatique pour reconnaître et classifier les espèces de fleurs à partir d'images, fournissant des informations détaillées pour faciliter l'identification des plantes.

Successfully established an image classification model using PyTorch to classify the images of several distinct natural sceneries such as mountains, glaciers, forests, seas, streets and buildings with an accuracy of 86%.