The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.
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Updated
Nov 7, 2023 - Python
The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
Convert images and videos to cartoons using opencv
A python implementation of KMeans clustering with minimum cluster size constraint (Bradley et al., 2000)
统计分析课程实验作业/包含《统计分析方法》中因子分析,主成分分析,Kmeans聚类等典型算法的手写实现
Implementing Genetic Algorithm on K-Means and compare with K-Means++
PyTorch implementations of KMeans, Soft-KMeans and Constrained-KMeans which can be run on GPU and work on (mini-)batches of data.
🍡 文本聚类 k-means算法及实战
This is a simple image clustering algorithm which uses KMeans for clustering and performs 3 types of vectorization using vgg16, vgg19 and resnet50 using the weights from ImageNet
Computer Vision - Impemented algorithms - Hybrid image, Corner detection, Scale space blob detection, Scene classifiers, Vanishing point detection, Finding height of an object, Image stitching.
An approach for finding dominant color in an image using KMeans clustering with scikit learn and openCV. The approach here is built for realtime applications using TouchDesigner and python multi-threading.
Python program to convert slices of 2D images to 3D structure
Simple k-means clustering (centroid-based) using Python
Federated k-means clustering algorithm implementation and proof of concept.
Repository containing all the codes created for the lab sessions of CSE3020 Web Mining at VIT University Chennai Campus
Python Implementation of k-means clustering
A data-driven tool to identify the best candidates for a marketing campaign and optimize it.
There are Python 2.7 codes and learning notes for Spark 2.1.1
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