Data Science by ODS.ai 🦜
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First Telegram Data Science channel. Covering all technical and popular staff about anything related to Data Science: AI, Big Data, Machine Learning, Statistics, general Math and the applications of former. To reach editors contact: @malev
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Jonker-Volgenant Algorithm + t-SNE = Super Powers: https://blog.sourced.tech/post/lapjv/

#tsne #visualization
πŸŽ‚πŸŽ‰New Release - #Matplotlib 3.0.0. Supports Python 3. Highlights include:

GUI backend is selected at run-time based on what toolkits are installed;
New cyclic color map *twilight*;
Improvements to automatic layout of titles, ticks & GridSpec.

mail thread: https://mail.python.org/pipermail/matplotlib-announce/2018-September/000027.html
official site: https://matplotlib.org/users/whats_new.html
installation: pip install -U matplotlib

#visualization #dataviz
​​Neural network 3D visualization framework. Very nice in-depth visualizations.

Now you can actually see how the layers look.

Github: https://github.com/tensorspace-team/tensorspace
LiveDemo (!): https://tensorspace.org/html/playground/vgg16.html

#visualization #nn
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California wildfire #visualization

How weather conditions during California's fire season have evolved over time.
​​Dimensionality reduction for visualizing single-cell data using UMAP

UMAP is an t-SNE replacement for #visualization.

UMAP is being increasingly accepted as a powerful tool for visualizing single cell datasets. This paper compares UMAP to #TSNE

While UMAP is unquestionably better than default t-SNE in preserving global structure, it's worth mentioning that (very recently) it was shown that this limitation of t-SNE appears to be addressable with better parameters/initialization.

Article link: https://www.nature.com/articles/nbt.4314
​​Exploring Neural Networks with Activation Atlases

Amazing interactive article on feature visualizations, letting us see through the eyes of the neural network. The hidden layers of neural networks are quite fun to inspect.

Interactive website: https://distill.pub/2019/activation-atlas/

#CV #DL #visualization
​​Model for tweaking graph visualization layout parameters

New #MachineLearning model builds a WYSIWYG interface to intuitively produce a layout you want!

Demo: http://kwonoh.net/dgl
Paper: http://arxiv.org/abs/1904.12225

#Visualization #ML
​​HiPlot: High-dimensional interactive plots made easy

Interactive parameters' performance #visualization tool. This new Facebook AI's release enables researchers to more easily evaluate the influence of their hyperparameters, such as learning rate, regularizations, and architecture.

Link: https://ai.facebook.com/blog/hiplot-high-dimensional-interactive-plots-made-easy
Github: https://github.com/facebookresearch/hiplot
Demo: https://facebookresearch.github.io/hiplot/_static/demo/demo_basic_usage.html
Pip: pip install hiplot

#hyperopt #facebook #opensource
​​Counting Happiness and Where it Comes From

Researches asked 10 000 Mechanical Turk participants to name 10 things which are making them happy, resulting in creation of HappyDB.

And since that DB is open, Nathan Yau analyzed and vizualized this database in the perspective of subjects and actions, producing intersting visualization.

Hope that daily reading @opendatascience makes you at least content, if not happy.

Happines reason visualization link: https://flowingdata.com/2021/07/29/counting-happiness
HappyDB link: https://megagon.ai/projects/happydb-a-happiness-database-of-100000-happy-moments/

#dataset #emotions #visualization
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