HOMER
Human Oriented autoMated machinE leaRning
Where: MI2DataLab at Warsaw University of Technology. Our GitHub.
With whom: Przemysław Biecek Google Scholar, GitHub.
What:
Machine learning models are used everywhere. Predictive modelling fundamentally changed data- driven disciplines like health-care, biology, finance, legal, military, security, transportation, and many more. The increasing availability of large annotated data sources combined with recent developments in machine learning models leads to the next industrial revolution.
BUT: Predictive models are handcrafted by data scientists in a tedious and laborious process. Most of the time spent on data exploration and model training is a set of try-and-error experiments. Models become more and more complex to catch even vague signals. Techniques like boosting, bagging or neural networks result in models with thousands or millions of parameters. Lack of understanding of complex models and poor automation results in problems with replicability and quality of models.
The main goal of this project is to develop new methods for human-oriented model exploration, interpretable model audits and automated model assembly. The newly appointed research team will create a grammar for human - model interaction.
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Send
to Przemyslaw.Biecek at gmail.