Credit Card Fraud Detection: Study and Implementation

This project is an application for classifying the quality of coconuts using the K Nearest Neighbors algorithm. It is built with Streamlit for easy deployment.

Here we are making a predictive system to measure the sentiment of each review or tweet, whether it is 1 (Positive Sentiment) or 0 (Negative Sentiment). In this work, LGBM Classifier, XGBooost Classifier, CatBoost Classifier, Random Forest Classifier, Gradient Boosting Classifier, K-Nearest Neighbors, and Logistic Regression are used.

Image classification in the gastrointestinal tract with KNN and CNN

Demonstrating different Machine Learning Model

A Python library of 'old school' machine learning methods such as linear regression, logistic regression, naive Bayes, k-nearest neighbors, decision trees, and support vector machines.

A swift implementation of a KNearestNeighbour Classifier in swift.

Data Science - K-Nearest Neighbors (KNN) Work

Esse pequeno projeto tem como objetivo fazer testes de acurácia com rede neural com apenas um neurônio sem classificadores e com 2 (dois) classificadores, sendo eles KNN e 1R.

Compared the metrics and performance of different classification algorithms on Heart Failure dataset from UCI ML Repository

Using Machine Learning to rank a list of customers most likely to buy a Car Insurance for a cross-sell campaign.

Project 1 for Introduction to Machine Learning course.

Self Work Coding Files related to Data Science

Sklearn, logistic regression, Naive Bayes classifier, K-Nearest Neighbors, decision trees

This is a repository to document my progress in learning the basics of common machine learning algorithms.

In this repository I am gonna show the main and most popular non-supervised clustering algorithms with short explanations.

The purpose of this project is to promote understanding -- my own and others' -- of fundamental data science and machine learning concepts and tools. It currently consists of one notebook that classifies fruit types based on weight, volume, and image data.

Build a Predictive model to forecast the sales of Rossmann store and uploaded the project to the challenge put forth by Rossmann Store

Implementation of the The k-nearest neighbors (KNN) algorithm. A machine learning algorithm that can be used to solve both classification and regression problems.