About the Project
A solution to this unnecessary scientific uncertainty will be automated machine learning. This automated machine learning should be able to imitate all aspects of human information acquisition: (i) learn (from experience or from data); (ii) unlearn (or forget information that is no longer valid); (iii) relearn (when previous information has not been corrected acquired); and (iv) be taught (via an optimal number of examples). There isn’t any complex methodology available which includes all these building blocks together and makes use of them. This will be the aim of this project, resulting in an easy to access framework for advanced data analysis and visualisation; an intelligent assistant which could interact with the user, could self-learn from experience based on similarity between the data analysed so far and which - based on a research on (already existing) research - could ensure the quality of the results through repetitive tests, automating the automation of knowledge discovery.
A strong computer science (machine learning) background is required as well as strong programming skills (Python, R, Java, C++).
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