K-Nearest-Neighbors

This project focuses on classifying listeners of a music website into adopters and non-adopters

Building a model for identifying potential Enron fraudsters based on financial and e-mail data with the use of Python. From data exploration to building and validating an algorithm.

Clustering engineering schools from data.gov API

CNIT 581-ATR Fall 2017 – Smart Cane Team: Wonse Jo and Shyam Sundar Kannan

Implementazione in R - C++. Progetto per il corso di Metodi Statistici per l'apprendimento.

Using classic machine learning models - K-NN, Multiclass Logistic Regression, SVM and Random Forest to make predictions

This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.

CS480F at Binghamton University with Dr. Ken Chiu

Machine Learning : Applied KNN on Breast Cancer data to find the result

This is a repository for implementing statistical learning models from scratch using the Python and Java programming languages.

Using k-nn classifier on the ionosphere dataset

DP-kNN: Short-Term Traffic Forecasting Using Self-Adjusting k-Nearest Neighbours

Clasificador de imagenes de bananas, naranjas y limones por medio de algoritmos de aprendizaje K-nn y K-means. Procesado de imágenes con SciKit y OpenCV.

Solved tasks of "Machine Learning" course, contains implementations of main machine learning algorithms.

Breast Cancer Prediction using K-NN, Machine Learning/Artificial Intelligence Algorithm on Python sckilearn