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Crime and Incarceration in the United States contain data on crimes that are committed, and the prisoner counts in every 50 states, for which the data is analyzed using various analytical methods.
To predict whether person has chronic Kidney disease or not chronic Kidney disease? • Predicted whether a patient will have chronic kidney disease or not, by using 24 predictors. • Used Decision Tree, Random Forest, XGBoost models for prediction. • Got an accuracy of 0.95 for XGBoost Model
In this project, the selling price of the houses have been predicted using various Regressors, and comparison charts have been shown that depict the performance of each model. This submission was ranked 107 out of 45651 in first attempt on Kaggle leader-board which can be accessed from here : https://www.kaggle.com/c/home-data-for-ml-course/lead…
A recommendation system created for H&M created with the help of EDA(Exploratory Data Analysis) and ALS (Alternative Least Squares) which optimizes a users recommendations taking into considerations an account`s view history and uses matrix optimization to give the best possible recommendations.
Breast Cancer Detection - This project tackles the crucial challenge of early breast cancer detection using machine learning techniques. Using Machine learnig algorithms, Support Vector Machine, Randon Forest.
Hi all! My project aims to predict customer conversion for an insurance company. The main objective of the project is to develop an accurate and efficient model that can aid the insurance company in improving its sales conversion rate and reducing marketing costs.
Crafted a machine learning model employing Support Vector Machine (SVM) algorithm to anticipate diabetes patterns using the diabetic prediction dataset. Dive into predictive analytics with this insightful project! 📊🔍