Speedxzk's repositories
pyMultiobjective
A python library for the following Multiobjective Objectives Optimization Algorithms or Many Objectives Optimization Algorithms: C-NSGA II; CTAEA; GrEA; IBEA; MOEA/D; NAEMO; NSGA II; NSGA III; OMOPSO; PAES; RVEA; SMPSO; SPEA2; U-NSGA III
PlotNeuralNet
Latex code for making neural networks diagrams
Support-Vector-Machines-and-Spam-Classifier
In this exercise, you will be using support vector machines (SVMs) to build a spam classifier. Files needed for this exercise ex6.mlx - MATLAB Live Script that steps you through the exercise Part 1 ex6data1.mat - Example Dataset 1 ex6data2.mat - Example Dataset 2 ex6data3.mat - Example Dataset 3 svmTrain.m - SVM training function svmPredict.m - SVM prediction function plotData.m - Plot 2D data visualizeBoundaryLinear.m - Plot linear boundary visualizeBoundary.m - Plot non-linear boundary linearKernel.m - Linear kernel for SVM submit.m - Submission script that sends your solutions to our servers *gaussianKernel.m - Gaussian kernel for SVM *dataset3Params.m - Parameters to use for Dataset 3 Part 2 spamTrain.mat - Spam training set spamTest.mat - Spam test set emailSample1.txt - Sample email 1 emailSample2.txt - Sample email 2 spamSample1.txt - Sample spam 1 spamSample2.txt - Sample spam 2 vocab.txt - Vocabulary list getVocabList.m - Load vocabulary list porterStemmer.m - Stemming function readFile.m - Reads a file into a character string submit.m - Submission script that sends your solutions to our servers *processEmail.m - Email preprocessing *emailFeatures.m - Feature extraction from emails
darknet
Yolo v4 (v3/v2) - Windows and Linux version of Darknet Neural Networks for object detection (Tensor Cores are used)
awesome-semantic-segmentation
:metal: awesome-semantic-segmentation
opencv
Open Source Computer Vision Library
RAdam
On The Variance Of The Adaptive Learning Rate And Beyond
standard_DE
Differential Evolution_Scheme DE1
tensorflow
Computation using data flow graphs for scalable machine learning