ycliper

Популярное

Музыка Кино и Анимация Автомобили Животные Спорт Путешествия Игры Юмор

Интересные видео

2025 Сериалы Трейлеры Новости Как сделать Видеоуроки Diy своими руками

Топ запросов

смотреть а4 schoolboy runaway турецкий сериал смотреть мультфильмы эдисон
Скачать

Alejandro Saucedo: Guide towards algorithm explainability in machine learning | PyData London 2019

Автор: PyData

Загружено: 2019-07-18

Просмотров: 5787

Описание: A practical guide towards algorithmic bias and explainability in machine learning.

Slides and code - https://github.com/EthicalML/explaina...

Undesired bias in machine learning has become a worrying topic due to the numerous high profile incidents. In this talk we demystify machine learning bias through a hands-on example. We'll be tasked to automate the loan approval process for a company, and introduce key tools and techniques from latest research that allow us to assess and mitigate undesired bias in our machine learning models.

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...

Не удается загрузить Youtube-плеер. Проверьте блокировку Youtube в вашей сети.
Повторяем попытку...
Alejandro Saucedo: Guide towards algorithm explainability in machine learning | PyData London 2019

Поделиться в:

Доступные форматы для скачивания:

Скачать видео

  • Информация по загрузке:

Скачать аудио

Похожие видео

Gianluca Campanella: The unreasonable effectiveness of feature hashing | PyData London 2019

Gianluca Campanella: The unreasonable effectiveness of feature hashing | PyData London 2019

All Machine Learning algorithms explained in 17 min

All Machine Learning algorithms explained in 17 min

Vincent Warmerdam: How to Constrain Artificial Stupidity | PyData London 2019

Vincent Warmerdam: How to Constrain Artificial Stupidity | PyData London 2019

Chris Fonnesbeck: An introduction to Markov Chain Monte Carlo using PyMC3  | PyData London 2019

Chris Fonnesbeck: An introduction to Markov Chain Monte Carlo using PyMC3 | PyData London 2019

Elina Naydenova: Bridging health inequalities through machine learning | PyData London 2019

Elina Naydenova: Bridging health inequalities through machine learning | PyData London 2019

САМЫЕ ОПАСНЫЕ ШУТКИ ЖВАНЕЦКОГО | Разборы

САМЫЕ ОПАСНЫЕ ШУТКИ ЖВАНЕЦКОГО | Разборы

Kevin Lemagnen: Maintainable code in data science | PyData London 2019

Kevin Lemagnen: Maintainable code in data science | PyData London 2019

Японец по цене ВАЗа! Оживляем пацанскую мечту :)

Японец по цене ВАЗа! Оживляем пацанскую мечту :)

Новый ChatGPT: от новичка до PRO за полчаса. Большой бесплатный курс.

Новый ChatGPT: от новичка до PRO за полчаса. Большой бесплатный курс.

Leland McInnes: UMAP, HDBSCAN & the Geometry of Data | Learning from Machine Learning #10

Leland McInnes: UMAP, HDBSCAN & the Geometry of Data | Learning from Machine Learning #10

© 2025 ycliper. Все права защищены.



  • Контакты
  • О нас
  • Политика конфиденциальности



Контакты для правообладателей: [email protected]