Optuna: A Define by Run Hyperparameter Optimization Framework | SciPy 2019 |

In this talk, we introduce Optuna, a next-generation hyperparameter optimization framework with new design-criteria: (1) define-by-run API that allows users to concisely construct dynamic, nested, or conditional search spaces, (2) efficient implementation of both sampling and early stopping strategies, and (3) easy-to-setup, versatile architecture that can be deployed for various purposes, ranging from scalable distributed computing to lightweight experiment conducted in a local laptop machine. Our software is available under the MIT license (github.com/pfnet/optuna/)
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[@user-ci7lf8pr1t]

Very useful library. Awesome.

[@Eriddoch]

Awesome library, and *fantastic* presentation! So many cool things that this does!

[@ihgnmah]

Cool library! Just added in my toolkits.

[@shandou5276]

What tool is being used to make this slide show that can run codes in the terminal?

[@corneliusemde8371]

is there a way to simply launch all these in one go? automatically launch 16 shells giving them each one of 8 GPUs s.t. i am automatically training with 2 processes per GPU?

[@bhishanpoudel8707]

The given code gives some deprecation warnings `Function fetch_mldata is deprecated;`

[@CircuitShepherd]

Hello there ;P