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kmeans-clustering
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Python code for common Machine Learning Algorithms
random-forest
svm
linear-regression
naive-bayes-classifier
pca
logistic-regression
decision-trees
lda
polynomial-regression
kmeans-clustering
hierarchical-clustering
svr
knn-classification
xgboost-algorithm
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Jul 18, 2021 - Jupyter Notebook
The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.
python
data-science
machine-learning
algorithms
modeling
batch-normalization
neural-networks
data-analysis
unsupervised-learning
kmeans-clustering
machine-learning-python
dbscan-clustering
regression-algorithms
k-nearest-neighbors
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Updated
Jun 4, 2021 - Python
Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means
neural-network
random-forest
linear-regression
machine-learning-algorithms
naive-bayes-classifier
supervised-learning
gaussian-mixture-models
logistic-regression
kmeans
decision-trees
knn
principal-component-analysis
dynamic-time-warping
kmeans-clustering
em-algorithm
kmeans-algorithm
singular-value-decomposition
knn-classification
gaussian-classifier
value-iteration-algorithm
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May 15, 2017 - MATLAB
A simple machine learning framework written in Swift 🤖
swift
machine-learning
neural-network
genetic-algorithm
linear-regression
machine-learning-algorithms
regression
artificial-intelligence
machine-learning-library
feedforward-neural-network
kmeans
ridge-regression
polynomial-regression
backpropagation
kmeans-clustering
mlkit
lasso-regression
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Aug 28, 2018 - Swift
kmeans using PyTorch
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Apr 20, 2021 - Jupyter Notebook
machine learning algorithm
hmm
log
svm
crf
linear-regression
dnn
id3
logistic-regression
cart
adaboost
bayes
gmm
rf
knn
softmax-regression
kmeans-clustering
memm
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Updated
Dec 31, 2020 - C++
Streaming Anomaly Detection Solution by using Pub/Sub, Dataflow, BQML & Cloud DLP
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Jan 21, 2021 - Java
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
machine-learning
linear-regression
machine-learning-algorithms
python3
pytorch
naive-bayes-classifier
pca-analysis
gaussian-mixture-models
logistic-regression
decision-trees
ridge-regression
naive-bayes-algorithm
kmeans-clustering
svm-classifier
lasso-regression
knn-classification
pytorch-implementation
tfidf-vectorizer
adaboost-algorithm
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Updated
Jul 7, 2021 - Python
Implemented ML algorithms in hyperbolic geometry (MDS, K-Means, Support vector machines, etc.)
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May 19, 2020 - Jupyter Notebook
A python implementation of KMeans clustering with minimum cluster size constraint (Bradley et al., 2000)
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Mar 2, 2021 - Python
An approach to document exploration using Machine Learning. Let's cluster similar research articles together to make it easier for health professionals and researchers to find relevant research articles.
machine-learning
random-forest
clustering
sklearn
kaggle
pca
classification
dimensionality-reduction
bokeh
kmeans
tsne
principal-component-analysis
kmeans-clustering
sgd-classifier
coronavirus
covid-19
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Dec 12, 2020 - HTML
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
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Feb 15, 2020 - Python
Super fast simple k-means implementation for unidimiensional and multidimensional data.
nodejs
javascript
fast
browser
cluster
kmeans
k-means
kmeans-clustering
multidimensional
kmeans-algorithm
centroid
k-means-clustering
unidimensional
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May 25, 2021 - JavaScript
Convert images and videos to cartoons using opencv
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Jan 12, 2021 - Python
Parallel & lightning fast implementation of available classic and contemporary variants of the KMeans clustering algorithm
clustering
julia
parallel-computing
kmeans-clustering
kmeans-clustering-algorithm
mlj
mlj-unsupervised
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Jun 29, 2021 - Julia
David Mackay's book review and problem solvings and own python codes, mathematica files
python
data-science
clustering-algorithm
kmeans-clustering
hamiltonian-monte-carlo
gibbs-sampling
maximum-likelihood-estimation
monte-carlo-sampling
mathematica-notebook
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Sep 19, 2017 - Jupyter Notebook
Personalized real-time movie recommendation system
real-time
movie
rating
collaborative-filtering
recommendation-system
movie-recommendation
movielens-dataset
kmeans-clustering
slope-one
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Jun 7, 2019 - Java
Performs an exploratory analysis on a dataset containing information about shop customers. Check that the assumptions K-means makes are fulfilled. Apply K-means clustering algorithm in order to segment customers.
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Feb 19, 2020 - Jupyter Notebook
Code for determining optimal number of clusters for K-means algorithm using the 'elbow criterion'
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May 11, 2021 - Jupyter Notebook
Computer Vision - Impemented algorithms - Hybrid image, Corner detection, Scale space blob detection, Scene classifiers, Vanishing point detection, Finding height of an object, Image stitching.
python
computer-vision
deep-learning
svm
corner-detection
transfer-learning
vgg16
image-stitching
googlenet
kmeans-clustering
hybrid-image
vanishing-points
resnet-50
blob-detection
knn-classification
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Jun 6, 2018 - Python
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Jan 22, 2019 - Python
Unsupervised Machine Learning: Nonnegative Tensor Factorization + k-means clustering
machine-learning
sparsity
feature-extraction
unsupervised-learning
kmeans-clustering
tensor-decomposition
cp-decomposition
blind-source-separation
tensor-networks
hosvd
tucker-decomposition
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Jul 27, 2021 - Julia
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
python
machine-learning
deep-learning
convolutional-neural-networks
kmeans-clustering
image-clusterization
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Dec 6, 2019 - Python
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.
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Aug 11, 2020 - Python
Implementing Genetic Algorithm on K-Means and compare with K-Means++
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Jun 14, 2021 - Python
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Hi I would like to propose a better implementation for 'test_indices':
We can remove the unneeded np.array casting:
Cleaner/New:
test_indices = list(set(range(len(texts))) - set(train_indices))
Old:
test_indices = np.array(list(set(range(len(texts))) - set(train_indices)))