Trying various machine learning method, it has the data set. Welcome to pull request
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Updated
Oct 19, 2017 - Python
Trying various machine learning method, it has the data set. Welcome to pull request
This script compares the accuracy of both KNN and Decision Tree and visualizes the same.
recognize the digits basic on sklearn, keras and pytorch
my solution to the third computer assignment of my intelligent systems course on the topic of clustering
Preditor de Sexo baseado em Peso e Altura e um identificador de dígitos usando KNN
Map-Reduce paradigm in Apache Hadoop for KNN algorithm based on Kaggle Titanic Dataset
Used PCA for dimension reduction of a 25x25 animal image dataset. After the feature extraction step, a KNN classifier to distinguish the images in a 3D plane (3PC extraction). PCA and KNN are implemented from scratch. Matplot is used for 3D visualization.
this app is going to be a cool web service that suggest similar music based on favorited music features
Text Recognition using Machine Learning.
Assignment for Machine Learning (Introduction to Classification, Search and Optimisation) (University of Malta) 2018/19 - Implementing and experimenting with k-Means and KNN using Python
WebApp implementada en Python, Flask y OpenCV para realizar búsquedas espaciales (KNN) sobre el dataset Labeled Faces in the Wild almacenado en una estructura RTree, encodificando los vectores característicos de un rostro arbitrario para realizar una búsqueda eficiente.
Machine Learning Algorithms in Python
Aplicação em Python de Reconhecimento de Dígitos utilizando algoritmo k-nearest neighbors (KNN).
A loan prediction model employing AI and data analysis to assist banks in determining loan approval, comparing various algorithms for accuracy.
This reposirtory is a 'Chat-with-your-PDF' project using RAG approach.
This repository contains implementations of various machine learning algorithms from scratch (KNN, MSE Linear Regression, SVM, Neural Networks, Logistic Regression). Each algorithm is implemented in Python and is contained in its own directory.
Identifying Image Orientation using Supervised Machine Learning Models of k-Nearest Neighbors, Adaboost and Multi-Layer Feed-Forward Neural Network trained using Back-Propagation Learning Algorithm
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