All Classical Machine Learning Algorithms and respective Case Study for each algo type.

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.

Evaluation and Implementation of various Machine Learning models for creating a "Banking/Financial Transaction Fraud Prevention System"

几种常见的特征分箱与可视化的方法

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 repository you can find the all the ML algorithm's notebook and notes.

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.

📊 Machine Learning - Hands-On Learning & Solved Notebooks This repository contains solved graded notebooks with test cases and ungraded practice notebooks covering core Machine Learning concepts, including Supervised & Unsupervised Learning, Advanced Learning Algorithms and more. Perfect for structured learning and hands-on practice! 🚀

machine-learning algorithms using Python.

No description provided.

Automated ML pipeline for Iris dataset classification using Decision Tree. Features PCA dimensionality reduction and standard scaling.

A visualization of Decision Tree and Random Forest algorithms using Python's Manim library

🚲 Predict bike rental counts in Seoul using regression models to enhance understanding of sharing demand based on weather and time features.

A classification model using "Fake news classification" dataset by Bhavik Jikadara for classifying fake news. Contributors: Elaha Ahmadi, Herman Scheele & Theodor Jaarvik

Prediction of customer will purchase iPhone or not using KNN classifier model and multiple supervised ML model.

🪐 6- Social Buss: Academic project for Fake News detection using Machine Learning algorithms applied to Portuguese language data, focused on testing and comparing supervised models.

This repo features two AI-driven projects: a Python game that employs Min-Max and Alpha-Beta pruning algorithms for strategic gameplay, and a Prolog-based expert system designed for optimizing water resource management using decision trees.

Breast Cancer Detection: This project uses machine learning techniques to classify breast cancer as malignant or benign based on features extracted from breast mass biopsies. Models used include SVM, Decision Tree, Naive Bayes, and K-Nearest Neighbors.

Credit Risk Analysis : Classification Models that can predict if a loan is likely to default using Decision Trees/Ensemble methods

Capstone project 2-Bike sharing demand prediction. The goal of this project is to build a ML model that is able to predict the demand of rental bikes in the city of Seoul.

Credit card fraud detection model that is built using Machine Language and R programming

Heart Disease Prediction App is a machine learning web application that predicts the likelihood of heart disease based on user medical inputs. Built using a Decision Tree Classifier and deployed with Streamlit for an interactive, user-friendly interface.

A machine-learning-based disease prediction app that analyzes symptoms to provide accurate, timely health insights for proactive care.