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dimensionality-reduction
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Practice and tutorial-style notebooks covering wide variety of machine learning techniques
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deep-learning
neural-network
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numpy
naive-bayes
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pandas
artificial-intelligence
classification
dimensionality-reduction
matplotlib
decision-trees
principal-component-analysis
k-nearest-neighbours
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Aug 19, 2020 - Jupyter Notebook
Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.
python
bioinformatics
analysis
clustering
gene-expression
data-visualization
dimensionality-reduction
awesome-list
data-integration
atac-seq
single-cell
rna-seq-data
scrna-seq-data
cell-cycle
cell-differentiation
gene-expression-profiles
analysis-pipeline
cell-populations
rna-seq-experiments
cell-clusters
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Aug 4, 2020
A curated list of community detection research papers with implementations.
data-science
machine-learning
deep-learning
social-network
clustering
community-detection
network-science
deepwalk
matrix-factorization
networkx
dimensionality-reduction
factorization
network-analysis
unsupervised-learning
igraph
embedding
graph-clustering
node2vec
network-clustering
bigclam
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Aug 4, 2020 - Python
Text Classification Algorithms: A Survey
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random-forest
text-classification
recurrent-neural-networks
naive-bayes-classifier
dimensionality-reduction
logistic-regression
document-classification
convolutional-neural-networks
text-processing
decision-trees
boosting-algorithms
support-vector-machines
hierarchical-attention-networks
nlp-machine-learning
conditional-random-fields
k-nearest-neighbours
deep-belief-network
rocchio-algorithm
deep-neural-network
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Jun 15, 2020 - Python
Extensible, parallel implementations of t-SNE
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Aug 4, 2020 - Python
machine-learning
clustering
som
neural-networks
dimensionality-reduction
outlier-detection
unsupervised-learning
manifold-learning
self-organizing-map
vector-quantization
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Aug 19, 2020 - Python
Using siamese network to do dimensionality reduction and similar image retrieval
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Jul 22, 2019 - Jupyter Notebook
An R package implementing the UMAP dimensionality reduction method.
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Aug 3, 2020 - R
Dimensionality reduction in very large datasets using Siamese Networks
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Jun 15, 2020 - Python
A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)
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Jul 24, 2020 - Julia
Machine Learning notebooks for refreshing concepts.
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reinforcement-learning
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deep-learning-algorithms
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regression-models
deep-learning-tutorial
data-science-notebook
model-evaluation
classification-trees
clustering-methods
machine-learning-tutorials
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Oct 31, 2018 - Jupyter Notebook
A repository of pretty cool datasets that I collected for network science and machine learning research.
data-science
benchmark
machine-learning
community-detection
network-science
deepwalk
dataset
dimensionality-reduction
network-analysis
network-embedding
link-prediction
gcn
node2vec
graph-embedding
node-classification
graph2vec
node-embedding
graph-convolution
gnn
graph-neural-network
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May 21, 2020
JavaScript implementation of UMAP
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Mar 6, 2020 - JavaScript
yuki-koyama
commented
May 9, 2018
It would be nice if it supports Thin Plate Spline (TPS) interpolation.
A sparsity aware implementation of "Deep Autoencoder-like Nonnegative Matrix Factorization for Community Detection" (CIKM 2018).
data-science
machine-learning
deep-learning
clustering
word2vec
sklearn
community-detection
deepwalk
autoencoder
dimensionality-reduction
unsupervised-learning
cikm
embedding
nmf
coordinate-descent
node2vec
node-embedding
gemsec
mnmf
danmf
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May 31, 2020 - Python
t-Distributed Stochastic Neighbor Embedding (t-SNE) in Go
visualization
go
data-science
machine-learning
dimensionality-reduction
unsupervised-learning
tsne
3d
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Jul 8, 2020 - Go
An implementation of demixed Principal Component Analysis (a supervised linear dimensionality reduction technique)
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Jul 30, 2020 - Jupyter Notebook
[Under development]- Implementation of various methods for dimensionality reduction and spectral clustering implemented with Pytorch
pytorch
dimensionality-reduction
graph-cut
diffusion-maps
pytorch-tutorial
diffusion-distance
laplacian-maps
fiedler-vector
pytorch-demo
pytorch-numpy
sorting-distance-matrix
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Oct 6, 2017 - Python
python
markov-model
hmm
analysis
clustering
molecular-dynamics
feature-extraction
pca
msmbuilder
dimensionality-reduction
tica
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Aug 4, 2019 - Python
Codes and Project for Machine Learning Course, Fall 2018, University of Tabriz
python
machine-learning
clustering
linear-regression
regression
neural-networks
supervised-learning
pca
classification
dimensionality-reduction
logistic-regression
recommender-system
gradient-descent
support-vector-machines
backpropagation
anomaly-detection
unsupervised-machine-learning
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Jan 10, 2019 - Jupyter Notebook
A New, Interactive Approach to Learning Data Science
python
machine-learning
random-forest
regression
datascience
dimensionality-reduction
feature-engineering
data-preparation
machine-learning-pipelines
binaryclassification
clusteranalysis
hyperparameter-tuning-
ensemble-learning-
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Aug 19, 2020 - Jupyter Notebook
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Aug 19, 2019 - Jupyter Notebook
Uniform Manifold Approximation and Projection - R package
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Jun 6, 2020 - R
A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).
machine-learning
deep-learning
word2vec
deepwalk
dimensionality-reduction
gensim
edge-prediction
multiscale
graph-mining
embedding
node2vec
word-embedding
graph-embedding
node-classification
graph-neural-networks
node-embedding
walklet
graphlet
dont-walk-skip
graph-convolution
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May 31, 2020 - Python
Ensemble topic modelling with pLSA
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Aug 4, 2020 - Python
Similarity Weighted Nonnegative Embedding (SWNE), a method for visualizing high dimensional datasets
bioinformatics
statistical-methods
data-visualization
dimensionality-reduction
single-cell-genomics
single-cell-rna-seq
nonnegative-matrix-factorization
single-cell-analysis
single-cell-atac-seq
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Jul 9, 2020 - R
Python Wrapper for t-SNE Visualization
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Jan 12, 2018 - Python
Python library for Self-Organizing Maps
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Jul 2, 2019 - Python
Local Fisher Discriminant Analysis in R
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Jul 10, 2020 - R
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Following up on the discussion here, it would be good to document how to get reproducible results with UMAP.
I think we should consider changing
random_statein the UMAP constructor to a seed (e.g. 42, like the newtransform_seeddefault) so that UMAP is reproducible by default.We should document that users can set `ran