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Running machine learning initiatives is difficult. Why? It is not possible for data scientists and teams to manage reproducibility, loss of IP, visibility and t...
To view the code, training visualizations, and more information about the python example at the end of this post, visit th...
Check out part 1 (here)and part 2 (here) of this series In the last part of our series on uncertainty estimation, we addressed the limitations of approaches like bootstrapping for larg...
You can check out part 1 of this series here In part 1 of this series, we discussed the sources of uncertainty in machine learning models, and techniques to quantify uncertain...
Authors: Drake Johnson (drakej@stanford.edu), Tim Ngo (ngotm@stanford.edu), Augusto Fernandez (afyrxr@stanford.edu) I. In...
Hosted by: Comet.ml and Pearl Cohen This week, we hosted a webinar with the patent experts at Pearl Cohen. During the webinar, Pearl Cohen talks about: Challenges to be aware of when...
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