​​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

Our channel audience data

On 9th of February we announced that we are going to share the results of the audience research with you. And here is the release. Please feel free to open issues, suggest improvements or corrections and submit pull requests.

Stay tuned for further releases, we are going to develop concept of Ultimate posts in the form of updated github repositories, containing all the best information, insights and materials on various topics.

Project github pages site: https://open-data-science.github.io/ods_channel_stats_eda/
Github: https://github.com/open-data-science/ods_channel_stats_eda
Non-verbous audience stats: https://open-data-science.github.io/ods_channel_stats_eda/research_eda_concise_version.html

#audience #eda #opensource #introspect