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1/ Excited to share something I've been working on for a while now. Troubleshooting Deep Neural Networks: a decision tree for debugging your model and improving performance.http://josh-tobin.com/troubleshooting-deep-neural-networks …
2/ I wrote this to codify some (often painful) lessons I learned as I got started in deep learning. Hope it can help others avoid some of my mistakes. Thanks to my coworkers at @berkeley_ai and @OpenAI, and especially @sergeykarayev and @pabbeel for helping me put this together.
3/ I’d love your feedback. What are your favorite DL debugging / troubleshooting tricks? Will share an updated version with everyone’s suggestions.
4/ A few other great resources on this topic I've seen: @AndrewYNg's http://mlyearning.org , @karpathy's thread https://twitter.com/karpathy/status/1013244313327681536 …, and this blog post https://pcc.cs.byu.edu/2017/10/02/practical-advice-for-building-deep-neural-networks/ …
Very helpful guide. Another debugging trick for the notebook users is: when Exception, create a new cell with %debug, it will jump you right back in where the Exception occur with all the values ready to be inspected.
nice, never knew that!
Thanks! looks very nice. Is there by any chance non ppt version?
Slides are in pdf, that’s all at this point, may turn it into a blog post some day
The best part is how it validates the soul-crushing frustration that comes naturally with deep learning. Thank you!
Really useful tool.
Valid points.
Wonderful guide! Will be extremely useful. Thank you
Thank you very much for taking the time to do this! Like many, I am getting started in DNN, and this will be a very useful tool for my learning! I really appreciate that some people take the time to make this knowledge more and more accessible!
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