A powerful tree-based uplift modeling system.
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Updated
Jan 23, 2024 - C++
A powerful tree-based uplift modeling system.
Web editor for typed tree structures. (like decision / behaviour trees)
Breast cancer detection using 4 different models i.e. Logistic Regression, KNN, SVM, and Decision Tree Machine Learning models and optimizing them for even a better accuracy.
Insurance claim fraud detection using machine learning algorithms.
Smart disease prediction system made using traditional machine learning algorithms and to create an user interface using streamlit. 🚀
A web application to predicted whether a URL/Website is phishing or not by extracting its lexical features.
This study demonstrates how numerous factors have an impact on bike rentals. Due to our understanding that many Koreans hire bikes throughout the week, we assumed that most of their use is for commuting to work or school. The number of rentals varies depending on a number of factors, including the day of the week, the hour of the day.
In this data science project, we will predict borrowers chance of defaulting on loans by building a default prediction model.
In this regression project, We will make use of different features like age, BMI, region, sex, smoker, etc to predict the medical insurance cost for an individual.
Unity package for generating 'treescheme' files based on dotnet assemblies.
Evaluation and Implementation of various Machine Learning models for creating a "Banking/Financial Transaction Fraud Prevention System"
machine-learning algorithms using Python.
A repository containing an advanced Excel project leveraging the "Heritage Dairy Company" dataset, showcasing visualizations and insights derived from the data for global distribution analysis and forecasting.
Prediction of customer will purchase iPhone or not using KNN classifier model and multiple supervised ML model.
This repository contains all resources for Homework 1 of TDT4173 fall 2021.
In this notebook, I'm using this dataset called 'flight-price-prediction', which contains the traveller information.In this notebook, I'm trying to run a dummy variable regression model at first, and after that, I'm trying to build a supervised ML Model with higher accuracy of predation.
Code for my Medium article: "How you can quickly deploy your ML models with FastAPI"
This project predicts iPhone purchases using demographic data (gender, age, salary). A Decision Tree Classifier was used, achieving 88.16% accuracy. Insights from the model can refine marketing strategies, optimize product offerings, and boost sales by targeting key customer segments.
This project presents and discusses data-driven predictive models for predicting the defaulters among the credit card users.About Data Cleaning,Exploratory Data Analysis ,Handling Class Imbalance, Transforming Data , Fitting Different Model ,Cross Validation & Hyperparameter Tunning, Comparison of Model ,Combined ROC Curve, Feature Impotance.
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