Maria Navarro: Quantifying uncertainty in Machine Learning predictions | PyData London 2019

Опубликовано: 18 Июль 2019
на канале: PyData
7,615
205

Slides - https://www.slideshare.net/MariaIsabe...

It is common practice to test the performance of ML models, but it is not so common to test the reliability of the predictions. Training a model, test its performance and hoping that it will produce good quality predictions is not the right approach if we are concerned with reliable ML. Hence, in this talk, we will discuss the concept of conformal predictions which quantify quality in predictions.

www.pydata.org

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases. 00:00 Welcome!
00:10 Help us add time stamps or captions to this video! See the description for details.

Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVi...


Смотрите видео Maria Navarro: Quantifying uncertainty in Machine Learning predictions | PyData London 2019 онлайн, длительностью часов минут секунд в хорошем качестве, которое загружено на канал PyData 18 Июль 2019. Делитесь ссылкой на видео в социальных сетях, чтобы ваши подписчики и друзья так же посмотрели это видео. Данный видеоклип посмотрели 7,615 раз и оно понравилось 205 посетителям.