This is a Malware Detection ML model made using Random Forest Algorithm

Training ensemble machine learning classifiers, with flexible templates for repeated cross-validation and parameter tuning

The objective of this project is to determine the risk of default that a client presents and assign a risk rating to each client. The risk rating will determine if the company will approve (or reject) the loan application

Predict whether a person will default on a loan or not.

Before training a model or feed a model, first priority is on data,not in model. The more data is preprocessed and engineered the more model will learn. Feature selectio one of the methods processing data before feeding the model. Various feature selection techniques is shown here.

👩Women👩 and 🎗 Breast Cancer🎗: Analysis📊 and Detection🔍

This is my Hamoye Stage C tag-along project. The notebook focuses on applying Machine Learning Classification models and Measuring Classification Performance.

This repository contains all the Machine learning [RTA] project | implimentation part done by The Bright Kid

Halo! Selamat datang di repository ku. Ini adalah model klasifikasi gagal jantung yang mempunyai akurasi sebesar 89% dengan algoritma Bagging! -Final Project H8

In this project, we design a robust activity recognition system based on a smartphone.

Machine Learning models for helping BNP Paribas Cardif accelerate its claims process

Web API in Python with Flask to classify wine with model created by extra-trees classifier algorithm.

Diabetes mellitus, commonly known as diabetes is a metabolic disease that causes high blood sugar. The hormone insulin moves sugar from the blood into your cells to be stored or used for energy. With diabetes, your body either doesn’t make enough insulin or can’t effectively use its insulin.

🚀 Developed a Python-based ML model for SMS and Email spam detection using NLP. Achieved high accuracy and precision! 📧🤖🔍 #MachineLearning #NLP #SpamDetection

Modelo em IA que classifica se um cogumelo é ou não venenoso

I developed a Leaf Disease Detection system using image processing techniques and tried to improve its performance using a MPI Cluster by using 2 Virtual Machines. In this project a performance analysis is also done to know about how much the speedup takes place when the system is run on a single node (1 VM) and on a 2-node cluster (2 VMs). I ha…

Predicting the stability of electrical grids using a binary classification model.

Used different types of machine learning classifiers such as Passive Aggressive, Extra Trees, Dummy Classifier to detect the DDos attack and compared the accuracies of the classifiers to determine the best out of the three.