Plain python implementations of basic machine learning algorithms
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Updated
Jun 27, 2024 - Jupyter Notebook
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
An implementation of the K-Nearest Neighbors algorithm from scratch using the Python programming language.
Source codes and datasets used for the undergraduate capstone project entitled "Machine Learning Algorithms for the Detection of GPS Spoofing in Intelligent Transportation Systems"
Machine Learning Algorithms
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
CSE601 Course Projects - Fall 2017
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.
Maching Learning Project : A classification problem using K Nearest Neighbor(KNN), Decision Tree, Support Vector Machine, and Logistic Regression algorithms
Sentiment analysis on Rotten Tomatoes Dataset
Integrating NNK evaluation with VISSL framework
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