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
Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
Fast and lightweight header-only C++ library (with Python bindings) for approximate nearest neighbor search
My solution to TUM's Machine Learning MNIST challenge 2016-2017 [winner]
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.
In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.
An implementation of the K-Nearest Neighbors algorithm from scratch using the Python programming language.
Driver drowsiness is one of the causes of traffic accidents. According to the statistics; highway road crashes hold 11.09% of the total number of accidents. There are several reasons of drowsy driving such as: a lack of quality of sleep, may be overnight driving or having sleep disorders e.g. sleep apnea. However; all people should know that: Pe…
TFG realizado en la Universidad de Burgos del desarrollo de una aplicación para el uso de un Radar de 60 GHz de la marca Acconeer.
Tour of Machine Learning Algorithms for Binary/Multiclass Classification
A robust classifier for few-training-data problem based on a distributionally robust optimization framework
Nearest neighbor search. Methods: LSH, hypercube, and exhaustive search. C++
GeoAdEx: A geometric approach for finding minimum-norm adversarial examples on k-NN classifiers
PyTorch implementation of following: Transfer Learning, Feature Extraction from deep network, k-NN
Diverse algorithms related to Machine Learning
A basic fruit sorter using k-means and k-nn.
Using classic machine learning models - K-NN, Multiclass Logistic Regression, SVM and Random Forest to make predictions
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.
Built a voice-controlled car from scratch incorporating machine learning methods such as the Euclidean Classifier and k-NN Classifier, open and closed loop feedback control systems, principal component analysis, regression analysis, and transient analysis
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