This project implements a computer vision-based fall detection system using deep learning techniques. The system can detect whether a person has fallen in images or video frames.

This study aims to explore the adoption of Google Play store Apps Data Analysis and Prediction models of the Google Play store apps data using Exploratory Data Analysis (EDA) which include the Data Analysis Techniques and implementation of Machine Learning methodologies to explore some critical analysis and insights using Python.

Machine Learning-based Insurance Claim Predictor that estimates insurance claim amounts using customer health and demographic data with an interactive Streamlit dashboard and data visualization.

A Python project that reads historical sea level data, creates scatter plots, and fits regression lines to visualize past trends and predict future sea level rise up to 2050.

This repository contains two machine learning projects that demonstrate my expertise in developing, tuning, and evaluating machine learning models from scratch. Each notebook showcases a different approach to solving real-world data-driven problems, from simple models to more advanced techniques.

This repo consists the implementation of Ant-Colony-Optimization algorithm written in python and helps to find optminal path in travelling salesman problem

🎯 A machine learning web app built with Streamlit to predict telecom customer churn based on usage and service features. It compares Logistic Regression, KNN, SVM, and Random Forest with full evaluation, visualizations, and a live demo.

Mutual Fund Analysis Dashboard using Python, Excel & Power BI | Top 30 Low-Risk High-Return Schemes

This is a python script retrieving Covid-19 cases in Egypt always up to date Confirmed cases , deaths and Recovered

Análisis de patrones clave en ventas de videojuegos para la tienda online ICE, usando datos históricos hasta 2016 para predecir ventas en 2017 y optimizar marketing.

A collection of Jupyter notebooks, scripts, and small projects for learning and experimenting with machine learning concepts. This repo is a sandbox for exploring algorithms, libraries, and techniques through focused experiments.

Loan Satuts

Comparing data about venues from different social networks

RU Анализ выручки и поведения пользователей Яндекс Афиши с использованием критерия Манна — Уитни

Config files for my GitHub profile.

This project predicts Titanic survivors using classification models. It includes data cleaning, pre-processing, exploratory data analysis (EDA), categorical feature conversion, model building, and evaluation. Python libraries like Pandas, NumPy, Matplotlib, and Seaborn are used to analyze and predict survival outcomes.

Data Dash is a marketing consulting company that specializes in the mining of and analysis of social media data. Compiled a dataset of possible influencers, used Tweepy (Twitter) API and Vader Sentiment analysis to produce a list of potential spokespersons that have the most potential as influencers based on a combination of number of followers,…

Practicing the knowledge of data cleaning and EDA of Titanic dataset

Collection of Python notebooks for practicing NumPy, Pandas, Exploratory Data Analysis (EDA), and data preprocessing.

A full-stack linguistic intelligence suite & forensic reporting tool. Features a "Dual-Engine" architecture (Django + DuckDB) for real-time text analysis, global etymology mapping, and persistent history storage.