Plain python implementations of basic machine learning algorithms

Interactive K-Nearest Neighbors machine learning algorithm in JavaScript.

implement the machine learning algorithms by python for studying

Data Mining Algorithms with C# using LINQ

Generic RTree for Nim

This toolbox offers 8 machine learning methods including KNN, SVM, DA, DT, and etc., which are simpler and easy to implement.

Adversarial Examples on KNN (and its neural network friends)

Calibration of an air pollution sensor monitoring network in uncontrolled environments with multiple machine learning algorithms

Source codes and datasets used for the undergraduate capstone project entitled "Machine Learning Algorithms for the Detection of GPS Spoofing in Intelligent Transportation Systems"

An implementation of the K-Nearest Neighbors algorithm from scratch using the Python programming language.

Machine Learning Algorithms

Integrating NNK evaluation with VISSL framework

Official Repository for the MELBA paper entitled "Dimensionality Reduction and Nearest Neighbors for Improving Out-of-Distribution Detection in Medical Image Segmentation".

CSE601 Course Projects - Fall 2017

Deep Learning breast histology microscopy image recognition using Convolutional Neural Networks

Syracuse University, Masters of Applied Data Science - IST 736 Text Mining

This is a repository for data science templates. New templates will be added as and when they are created. Feel free to use these templates for your data science projects!

📌 1. Compute the Mahalanobis distance from a centroid for a given set of training points. 2. Implement Radial Basis function (RBF) Gaussian Kernel Perceptron. 3. Implement a k-nearest neighbor (kNN) classifier

Various machine learning algorithm implementation tastes made of Python and Numpy. Enjoy!

A Python Machine Learning classification task to predict fall incidents in elderly persons taking into account reports and clinical information. The prediction application is live and usable on Streamlit to predict the possibility of falls in elderly persons.

Sentiment analysis on Rotten Tomatoes Dataset

Exploratory Data Analysis of MNIST dataset

Using SciKit Learn few Deep Learning Rules and Algorithms are implemented

This script analyzes and visualizes signal distribution in Banten using GeoPandas, Matplotlib, and NetworkX.

Sentiment Analysis on Movie Reviews Challenge

Maching Learning Project : A classification problem using K Nearest Neighbor(KNN), Decision Tree, Support Vector Machine, and Logistic Regression algorithms

Demo for KNN(K-Nearest Neighbor) & Iris module(a classical test) in data analysis in Python

K Nearest Neighbor (KNN) from scratch untuk pendukung keputusan penerima modal UMKM

The creation of the credit score models of a lending company.

This project uses the K-Nearest Neighbors (KNN) algorithm to classify Iris flowers based on their sepal and petal measurements. The dataset used in this project is the Iris Dataset, which includes 150 samples of Iris flowers, each with four features: sepal length, sepal width, petal length, and petal width.