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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.
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.
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.
In this project i am trying to use NLP, ML concepts on Amazon reviews using various ML based model like XGBoost, Decision tree classifier and random forest
Salary Prediction API using Flask predicts salaries for freshers joining organizations based on factors like past experience, company switches, courses completed, and academic marks. This Flask-based API allows users to input their details and receive a salary prediction. With no user interface, it's designed for integration into other applications
We have used our skill of machine learning along with our passion for cricket to predict the performance of players in the upcoming matches using ML Algorithms like random-forest and XG Boost
Applying boosting techniques such as GradientBoostingClassifier, GradientBoostingRegressor (eXtreme Gradient Boosting (XGBClassifier and XGBRegressor functions). This repo contains class examples and the project.
The Food Price Estimation project focuses on providing estimates of food prices to capture local price fluctuations in regions where people are vulnerable to localized price surges. The project utilizes a machine-learning algorithm designed to predict ongoing subnational price surveys, demonstrating accuracy comparable to direct price measurements.