Elsayed-Elmandoh's Projects
About me
This project is designed to explore the capabilities of generative models in content creation and image generation for blog posts.
This project involves performing an exploratory data analysis (EDA) on Airbnb listings data for a specific city. The analysis aims to identify trends, patterns, and insights within the dataset related to factors such as price, availability, location, and property types.
This project focuses on abstractive text summarization for the Arabic language using state-of-the-art transformer-based models. The goal is to develop a model capable of generating concise and meaningful summaries for given paragraphs. Competition Military Technical College
This repository is your comprehensive guide to building Artificial Neural Networks (ANN) using various frameworks in Python. Explore building ANNs from scratch using NumPy, implementing ANNs with TensorFlow, and creating ANNs with PyTorch.
A simple tool for automatic image annotation using Roboflow API
This is an Automated EDA (Exploratory Data Analysis) Tool built using Streamlit, the tool provides an interactive interface to perform various data analysis tasks without writing extensive code.
This project is an end-to-end automated machine learning (AutoML) model that streamlines the process of building, evaluating, and visualizing machine learning models for both classification and regression tasks. It is designed to help users with minimal data science expertise quickly go from raw data to a well-performing machine learning model.
Card Match Challenge is python game project implementing a card matching game using tkinter. Tests memory and strategy skills. Demonstrates game development, UI design, and Python proficiency.
This project is a code evaluator that can take input from the user as follows: Task description and Code (solution). The output will be a code evaluation.
This repository serves as your comprehensive guide to understanding and implementing Computer Vision techniques using Python. Dive into various topics, from basic introductions to advanced techniques, to gain a deeper understanding of processing and analyzing images.
This project focuses on customer segmentation and personalization in the context of an e-commerce business. It uses machine learning techniques, specifically K-means clustering and PCA, to identify distinct groups of customers with similar preferences and behaviors.
This project aims to create a set of Streamlit dashboards for visualizing and analyzing data within an organization's system. The dashboards provide interactive insights into user activity, subscriptions, course completion, capstone evaluations, coupon usage, and employment grant status.
This repository is your comprehensive guide to building and working with deep neural networks (DNNs) in Python. Explore a wide range of topics, from generating and preprocessing data to training and inference, as well as advanced techniques such as embedding layers, convolutional neural networks (CNNs), long short-term memory networks (LSTMs).
Develop a comprehensive machine learning and computer vision system that can detect potential terrorists in a given environment By classifying people as civilians or military and see whether they are carrying weapons or not.
This repository is dedicated to the exploration and analysis of datasets using Python. Whether you're a data scientist, analyst, or enthusiast, here you'll find resources, examples, and techniques for uncovering insights from data.
GemiLla is a Streamlit-based project that allows two conversational agents, Gemini and LLaMA, to engage in interactive discussions. It demonstrates the integration of Google Generative AI and Meta's LLAMA-3, providing an engaging and flexible conversation interface.
The Google AI Python SDK enables developers to use Google's state-of-the-art generative AI models (like Gemini and PaLM) to build AI-powered features and applications.
This project focuses on using neural networks to perform market segmentation based on customer demographics, behavior, and other relevant factors. Market segmentation is a crucial task for businesses looking to tailor their marketing strategies and offerings to specific customer segments.
Our AI-powered website analyzes health problems, connecting to wearables for continuous monitoring. It aids doctors in efficient diagnoses, expanding patient care capacity and enabling remote consultations, ensuring accessible and safe healthcare while creating job opportunities for doctors.
This project involves building a Convolutional Neural Network (CNN) model to analyze medical images, such as X-rays or MRIs, for detecting diseases or abnormalities. The goal is to develop a robust model that can accurately classify images into binary classes: normal or pneumonia.
This repository is your comprehensive guide to understanding and implementing Natural Language Processing (NLP) techniques in Python. Dive into various topics, from basic introductions to advanced techniques, to gain a deeper understanding of processing and analyzing text data.
OCR developed using CNN with Keras, TensorFlow, and Deep Learning is an image processing application that recognizes alphanumeric characters. This project is designed to extract text from images. making preprocessing and building the CNN model and training the model on the dataset. The trained model achieved an accuracy of 98% on the test set.
The Personal Assistant using OpenAI GPT-3 model is a revolutionary project in the field of artificial intelligence. It presents an intelligent assistant that can interact with users through both text and speech inputs, providing intelligent responses generated by the GPT-3 model.
Kolmogorov Arnold Networks
Dive into a collection of Python scripts. Whether you're a beginner looking to learn Python or an experienced developer seeking to expand your skills, you'll find valuable content and examples here to enhance your Python journey.
This Streamlit application performs recognition on ID images and extracts relevant information.
About me