Open the Black Box: an Introduction to Model Interpretability with LIME and SHAP - Kevin Lemagnen
PyData NYC 2018
What's the use of sophisticated machine learning models if you can't interpret them? This workshop covers two recent model interpretability techniques that are essentials in your data scientist toolbox: LIME and SHAP. You will learn how to apply these techniques in Python on a real-world data science problem.
===
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.
Видео Open the Black Box: an Introduction to Model Interpretability with LIME and SHAP - Kevin Lemagnen канала PyData
What's the use of sophisticated machine learning models if you can't interpret them? This workshop covers two recent model interpretability techniques that are essentials in your data scientist toolbox: LIME and SHAP. You will learn how to apply these techniques in Python on a real-world data science problem.
===
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.
Видео Open the Black Box: an Introduction to Model Interpretability with LIME and SHAP - Kevin Lemagnen канала PyData
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Scott Lundberg, Microsoft Research - Explainable Machine Learning with Shapley Values - #H2OWorldExplainable AI for Science and MedicineMulti-touch Attribution: What am I training for? - Sri Sri PerangurTalking Tech and AI with Google CEO Sundar Pichai!Kevin Lemagnen - Open the Black Box: an Introduction to Model Interpretability in PythonVincent Warmerdam: Winning with Simple, even Linear, Models | PyData London 2018Vincent D. Warmerdam: Untitled12.ipynb | PyData Eindhoven 2019AI Blog Post Summarization with Hugging Face Transformers & Beautiful Soup Web ScrapingA Bluffer's Guide to Dimension Reduction - Leland McInnesMore About Generators - James PowellInterpretable Machine Learning Using LIME Framework - Kasia Kulma (PhD), Data Scientist, AvivaPyData Tel Aviv Meetup: SHAP Values for ML Explainability - Adi WatzmanBuilding Explainable Machine Learning Systems: The Good, the Bad, and the UglyIf Brains are Computers, Who Designs the Software? - with Daniel DennettCustomer Lifetime Value: Models, Metrics and a Multitude of Uses - Brian BloniarzShapley Additive Explanations (SHAP)The Science Behind InterpretML: SHAPVincent Warmerdam: How to Constrain Artificial Stupidity | PyData London 2019SHAP - What Is Your Model Telling You? Interpret CatBoost Regression and Classification Outputs