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cv: January 11, 2022
webpage: January 11, 2022


Interpreting Black-Box Classifiers Using Instance-Level Visual Explanations
Paolo Tamagnini, Josua Krause, Aritra Dasgupta and Enrico Bertini
In Workshop on Human-In-the-Loop Data Analytics (HILDA), 2017

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Paolo Tamagnini

Data scientist specialized in guided analytics applications

paolotamag [at] gmail [dot] com

Data scientist with research experience, fond of data visualization and machine learning, currently working for KNIME in Berlin.

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Keywords: guided analytics; visual analytics; machine learning; data science; big data; Python; JavaScript; d3.js; KNIME; AWS; ...

In May 2018 I moved to Berlin to work as a data scientist in the evangelism team of KNIME. My work at KNIME is variegated, but it is particularly focused on guided analytics and automated machine learning. Since May 2021 I have been leading the Verified Components team of data scientists, releasing data science libraries, functions and tools via reusable and reliable KNIME workflows.

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Between November 2017 and February 2018 I worked on an open-source python library called partial_dependence in collaboration with Josua Krause and Enrico Bertini.

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In October 2017 I graduated at the Master (MSc) of Data Science from Sapienza University of Rome and my thesis is available here.

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In August 2016 I wrote my thesis in the research team of Enrico Bertini, associate professor at New York University, Tandon School of Engineering.

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