Spread the Word

Do you like using wandb? Here are some ways to share our tools with the world.

If you're enjoying our tools, please share wandb with your friends! We'd love for more people to use us.
Shout-Outs
​Twitter: tweet at us, our handle is @weights_biases
​Product Hunt: a review helps other people find our product
​Reddit: a post or comment on r/MachineLearning goes a long way
Thread 1: Experiment workflows​
Thread 2: ML framework​
Blog Posts
If you have a cool project or an insightful perspective you'd like to share, we love to amplify the work of our users. We can tweet about your blog post or host a post on our own blog. Please reach out at [email protected]
Product Feedback
File an issue in our open source GitHub repo: github.com/wandb/wandb. We love feedback, and we try hard to implement what users are asking for.
Thank You
We're so grateful to our users who have helped us improve the product and spread the word about Weights & Biases.
Who
Where
Links
Amir Abdi
UBC, Canada
​Disentanglement Challenge - the 3rd place repo 1st stage of the Disentanglement challenge of NeurIPS 2019
Sergey Kolesnikov
Moscow, Russia
​Catalyst - a high-level PyTorch API for DL & RL research
Sayak Paul
Kolkata, India
​Generating Categories from ArXiv Paper Titles - a TensorFlow project
Josh Tobin
San Francisco, California
​FSDL - a hands on course to bridge the gap from training machine learning models to deploying AI systems in the real world (We highly recommend!)
Whitman Bohorquez
Venezuela
​DeepBay - plug-n-play deep learning models
Boris Dayma
Houston, Texas
​CycleGAN - using deep learning to turn horses into zebras
Séb Arnold
USC, California
​Cherry - an RL framework built on top of PyTorch
Ryan Lee
Princeton, New Jersey
​End to End - a blog for machine learning projects
Róbert Csordás
IDSA, Switzerland
​W&B Profile - a published paper to come soon! :)
Peter Welinder
San Francisco
OpenAI robotics team

Who	Where	Links
Amir Abdi	UBC, Canada	Disentanglement Challenge - the 3rd place repo 1st stage of the Disentanglement challenge of NeurIPS 2019
Sergey Kolesnikov	Moscow, Russia	Catalyst - a high-level PyTorch API for DL & RL research
Sayak Paul	Kolkata, India	Generating Categories from ArXiv Paper Titles - a TensorFlow project
Josh Tobin	San Francisco, California	FSDL - a hands on course to bridge the gap from training machine learning models to deploying AI systems in the real world (We highly recommend!)
Whitman Bohorquez	Venezuela	DeepBay - plug-n-play deep learning models
Boris Dayma	Houston, Texas	CycleGAN - using deep learning to turn horses into zebras
Séb Arnold	USC, California	Cherry - an RL framework built on top of PyTorch
Ryan Lee	Princeton, New Jersey	End to End - a blog for machine learning projects
Róbert Csordás	IDSA, Switzerland	W&B Profile - a published paper to come soon! :)
Peter Welinder	San Francisco	OpenAI robotics team

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