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.
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Updated
Mar 23, 2025 - Python
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.
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.
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.
Loan Satuts
Practicing the knowledge of data cleaning and EDA of Titanic dataset
EDA on Student Performance
Config files for my GitHub profile.
🎯 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.
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.
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.
Comparing data about venues from different social networks
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.
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,…
A predictive analytics platform designed to transform retail inventory management through intelligent sales forecasting. SmartStock-Analytics leverages machine learning to predict demand for 50 products across 10 store locations, empowering retailers to strategically manage stock levels, allocate resources efficiently, and minimize inventory costs.
Data Wrangling Project from the Udacity Data Analytics Nano Degree
This project focuses on analyzing caste-based hate crimes using Python for data manipulation, Jupyter Notebook for exploratory data analysis (EDA), and Streamlit for creating an interactive web application to present insights.
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