random-forest-algorithm

In this project, we are going to use a random forest algorithm (or any other preferred algorithm) from scikit-learn library to help predict the salary based on your years of experience. We will use Flask as it is a very light web framework to handle the POST requests.

Understand and code some basic algorithms in machine learning from scratch

This repository contains the Machine Learning lessons I took from the Bootcamp between 10 Aug - 14 Sep 2022 and includes 17 sessions, 5 labs, 4 case studies, 5 weekly agendas, and 3 projects.

This project is about anomaly detection in social network, completely on network structure. We use random forest algorithm to train and test our classifier. Also, we are going to see how the effect of increase of trees in forest to the accuracy of prediction.

This repository contains the implementation of a machine learning project aimed at predicting the stage of cirrhosis based on clinical features.

Developed Random-Forest-based machine learning model to precisely predict gold prices, achieving 85% accuracy in testing conditions. Integrated large datasets to generate forecasts for near-term price fluctuations.

It is a ML based model to detect fake URLs and QR codes, using adv. data cleaning to improve accuracy. Built a Flask-based RESTful API for real-time fraud checks, allowing easy use in web and web apps. Designed a responsive JS front end to connect with the backend, showing fraud risk scores, confidence levels, and key risk factors for users

Build and Tune Several Models

Projects based on Machine Leaning

This system enhances safety with real-time health and position tracking using temperature and heart rate sensors, GPS, LoRa communication, and the Random Forest algorithm. Technologies include NodeMCU, Peltier modules, and LCD displays.

Analysis of the Restaurant reviews by using the Naive Bayes & the Random Forests Algorithms

Machine Learning algorithms. Generic code related to ML.

Analyse prior taxi geolocation and pricing data to predict future pricing

This is spark/Scala based Mobile Telecommunication Customer Churn Prediction model developed using Random Forest algorithm

Design and Implementation of Random Forest algorithm from scratch to execute Pacman strategies and actions in a deterministic, fully observable Pacman Environment.

Data analysis project on Digital Addiction for master thesis

Apprenticeship project with Indian Institute of Science. Objectives were to Model tumor and immune cell interaction in the presence of MMP & TIMP by varying their diffusion rates and check the effect of MMP8 on these interactions. These simulations provides insights into how ECM remodelling shapes cancer progression.

This is an example for how handwritten digits can be learnt with random forests

A machine learning model to predict the likelihood of heart disease based on medical attributes and lifestyle factors using algorithms like Logistic Regression, Decision Trees, and Random Forest for early detection and better healthcare outcomes.

Outfit Generator and Recommendation API