A robust classifier for few-training-data problem based on a distributionally robust optimization framework

Decision Tree & K-NN Classifiers implementations for ML Course @ ITBA

This program is a real-time face recognition system that uses OpenCV and k-Nearest Neighbors (k-NN) to detect and label faces from a webcam feed.

PyTorch implementation of following: Transfer Learning, Feature Extraction from deep network, k-NN

Predicting company bankruptcy using various machine learning models. The dataset is sourced from Kaggle: Company Bankruptcy Prediction.

KNN Is A Machine Learning Algorithm For Pattern Recognition That Finds The Nearest K Observations To Predict A Target.

Topographical Representation in an Associative Learning Task Using BSS Analysis on MEG Signals

Audio Pattern Recognition project - Music Genres Classification

a machine learning training project

Machine Learning tasks and mini projects based on my learning in a Datascience bootcamp in Udemy

A k-Nearest Neighbors (k-NN) Classifier for the Iris Flower Dataset implemented in Python using NumPy and SciPy. This project calculates distances between new and training samples, finds the k nearest neighbors, and predicts the types of new samples. Accuracy is evaluated against known labels.

Recommendation system using k-Nearest Neighbors algorithm (k-NN).

Benchmarks of collaborative filtering techniques and optimizing K-NN and SVD for recommendation accuracy

🤖 Machine Learning - Flores Iris | Modelos supervisionados para classificação de espécies

Machine Learning algorithms from scratch using C++

Using k-nn classifier on the ionosphere dataset

Comparing and finding the best model to predict the Status of a Loan Application.

Predictive Analytics Practice: Random Forest, K-NN, SVM, Regression, Logistic Regression

This machine learning initiative seeks to leverage the k-Nearest Neighbors (k-NN) classification algorithm to predict whether a Universal Bank will accept a personal loan offer.