Amr Khaled's Projects
About the man behind this account
This repository contains a convolutional neural network (CNN) model to solve a classification problem using images of butterflies. The goal is to predict the type of butterfly in the images. This project is part of a competition hosted on Kaggle.
This project is machine learning model that classifies credit scores using the RandomForestClassifier algorithm from scikit-learn.
This project is part of a Kaggle competition aimed at predicting whether a given tweet is about a disaster or a normal event. The solution involves preprocessing the tweet text data and training a Long Short-Term Memory (LSTM) model to classify tweets.
This project uses the VGG16 and EfficientNetB2 models to recognize facial emotions in the FER-2013 dataset, classifying expressions into seven emotions.
This repo is a football players detection and classification using YOLOv8 and RoboFlow for data creation
Fraud Detection machine learning model utilizes the "DecisionTreeClassifier" to identify fraudulent activities on an online payment app.
This repository contains a fine-tuning of the VGG16 pre-trained model to solve a classification problem using images of German traffic signs. The goal is to predict the type of traffic sign in the images. This project is part of a competition hosted on Kaggle.
This repo is my all HuggingFace Testing and Exploaring
This project on image processing uses enhancement and segmentation techniques to improve the training of computer vision models.
This project is a Python application that uses Optical Character Recognition (OCR) to extract text from images. It leverages the following libraries:
This repository is managed by LeetPush extension: https://github.com/husamahmud/LeetPush
This project demonstrates how to perform object detection and tracking on CCTV footage using YOLOv8 and Supervision libraries.
This module uses MediaPipe and OpenCV to perform real-time pose detection on video sources. It captures video from a webcam or a file, processes each frame to detect and draw human pose landmarks, and optionally saves the processed video to a file.
This model is designed to forecast website traffic using previous traffic.
This repository is (My study) for the zero_to_hero NLP course by TensorFlow on YouTube.