Lesson plan

Optuna

Optuna is an open-source Python library for automatic hyperparameter tuning of machine learning models. It was first introduced in 2018 by Preferred Networks, a Japanese startup that works on practical applications of deep learning in various fields. The beta version of Optuna was released at the end of the year, with the subsequent first major stable release announced in January 2020.

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Article summary

Optuna is an open-source Python library for automatic hyperparameter tuning of machine learning models. It was first introduced in 2018 by Preferred Networks, a Japanese startup that works on practical applications of deep learning in various fields. The beta version of Optuna was released at the end of the year, with the subsequent first major stable release announced in January 2020.

Key claims

  1. release date: 2020 — source: Wikipedia · confidence 0.95

Discussion questions

  1. Summarise the article in your own words. Which single claim would you verify first, and why?
  2. The record states that the release date is "2020". What evidence would count against this claim?
  3. Which claim in this article is most likely to be revised as the sources update? How would you check its current status?
  4. If two sources disagreed about one of these facts, what would you need in order to trust one over the other?

Bibliography

  1. Wikipedia https://en.wikipedia.org/w/index.php?oldid=1378747461

Key claims and bibliography are generated from the same tracked claims and sources as the article page.