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AI Nexus is a streamlined suite of AI-powered apps built with Streamlit. It includes StyleScan for fashion classification, GlycoTrack for diabetes prediction, DigitSense for digit recognition, IrisWise for iris species identification, ObjexVision for object recognition, and GradeCast for GPA prediction with detailed insights.
Data analysis and predictive modeling of global water supply trends using historical data from the United Nations Environment Statistics Database. This project explores water accessibility trends across countries and forecasts future water supply scenarios through machine learning techniques.
This study involves employing machine learning models and anomaly detection approaches, such as over- and under-sampling, to detect fraud in online transactions.
Our project employs machine learning to pinpoint phishing URLs with 97.4% accuracy, leveraging HTTPS and website traffic as critical indicators. Insights into features like AnchorURL enhance cybersecurity strategies, showcasing the power of AI in combating online threats.
Este projeto, desenvolvido durante o curso da Alura, utiliza o algoritmo XGBoost para prever a presença de doenças cardíacas em pacientes com base em um conjunto de dados clínicos. O modelo foi treinado e avaliado utilizando técnicas de validação cruzada e otimização de hiperparâmetros.
The T20 World Cup Score Prediction project aims to predict the total runs scored by a team in a T20 cricket match using the XGBoost algorithm. XGBoost is a popular machine learning algorithm used for predictive modeling.
This is a end to end Data Science project where the task is to predict the Fare of the flights (Indian Only). Data is in the form of Excel spreadsheets, one is for training purpose and the other is for testing.
Predict future movements from skeleton data. Utilize XGBoost classifier on time series of 3D skeleton data for tasks like fall detection or gesture recognition. Preprocess, train, evaluate, and predict for submission.
This repository presents a comprehensive analysis of bank customer financial product ownership using advanced machine learning techniques. The project leverages a rich dataset containing demographic information, product ownership details, and other relevant attributes such as country of residence, age, and gross income.
XGBoost (Extreme Gradient Boosting) is a highly efficient and accurate machine learning algorithm based on gradient boosting, excelling in structured data tasks. It includes features like regularization, handling missing values, and parallel processing. Widely used in competitions and industry, it supports multiple programming languages.
India is one of the countries with the highest air pollution country. Generally, air pollution is assessed by PM value or air quality index value. For my further analysis, I have selected PM-2.5 value to determine the air quality prediction and the India-Bangalore region. Also, the data was collected through web scraping with the help of Beautif…
The study focuses on modeling and predicting H5N1 bird flu outbreaks in the United States at the county level, utilizing diverse statistical techniques and machine learning models.