Publications by smarterpoland
DALEX has a new skin! Learn how it was designed at gdansk2019.satRdays
DALEX is an R package for visual explanation, exploration, diagnostic and debugging of predictive ML models (aka XAI – eXplainable Artificial Intelligence). It has a bunch of visual explainers for different aspects of predictive models. Some of them are useful during model development some for fine tuning, model diagnostic or model explanation...
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iBreakDown: faster, prettier and more precise explanations for predictive models (with interactions)
LIME and SHAP are two very popular methods for instance level explanations of machine learning models (XAI). They work nicely for images and text inputs, but share similar weakness in case of tabular data: explanations are additive while complex models are (sometimes) not. iBreakDown addresses this problem. iBreakDown is a a successor of the bre...
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Explore the landscape of R packages for automated data exploration
Do you spend a lot of time on data exploration? If yes, then you will like today’s post about AutoEDA written by Mateusz Staniak. If you ever dreamt of automating the first, laborious part of data analysis when you get to know the variables, print descriptive statistics, draw a lot of histograms and scatter plots – you weren’t the only one....
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DALEX for keras and parsnip
DALEX is a set of tools for explanation, exploration and debugging of predictive models. The nice thing about it is that it can be easily connected to different model factories. Recently Michal Maj wrote a nice vignette how to use DALEX with models created in keras (an open-source neural-network library in python with an R interface created by RS...
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Make it explainable!
Most people make the mistake of thinking design is what it looks like… People think it’s this veneer — that the designers are handed this box and told, ‚Make it look good!’ That’s not what we think design is. It’s not just what it looks like and feels like. Design is how it works. Steve Jobs, The New York Times, 2003. Same goes wit...
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How to design a model visualisation @ Gdansk satRdays
I had amazing weekend in Gdansk thanks to the satRday conference organized by Olgun Aydin, Ania Rybinska and Michal Maj. Together with Hanna Piotrowska we had a talk ,,Machine learning meets design. Design meets machine learning”. Hanna redesigned DALEX visualisations (DALEX is a set of tools for visual explanation of predictive ML models). Du...
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xaibot – conversations with predictive models!
If you could talk to a predictive machine learning model, what would you ask for? Try! Michał Kuźba is developing a mind-blowing project – xai chat-bot. Dialog based system that helps to explore and understand predictive models through natural language conversations (type, speak or phone the model ). For example, imagine that you have a rand...
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modelDown is now on CRAN!
The modelDown package turns classification or regression models into HTML static websites. With one command you can convert one or more models into a website with visual and tabular model summaries. Summaries like model performance, feature importance, single feature response profiles and basic model audits. The modelDown uses DALEX explainers. S...
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Learn about XAI in R with ,,Predictive Models: Explore, Explain, and Debug”
XAI (eXplainable artificial intelligence) is a fast growing and super interesting area. Working with complex models generates lots of problems with model validation (on test data performance is great but drops at production), model bias, lack of stability and many others. We need more than just local explanations for predictive models. The more c...
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dime: Deep Interactive Model Explanations
Hubert Baniecki created an awesome package dime for serverless HTML interactive model exploration. The experimental version is at Github, here is the pkgdown website. It is a part of the DrWhy.AI project. How does it work? With the DALEX package you can create local and global model explanations for machine learning models. Each explanation can b...
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