Paolo Tamagnini
Data Scientist // Data Evangelist // AI Engineer
paolotamag [at] gmail [dot] com
Keywords : visual analytics ; machine learning ; data science ; big data ; Python ; JavaScript ; LLMs ; low code ; ...
TL;DR : working in the KNIME evangelism team: teaching the software, presenting new trends, pampering advocates, collaborating with universities, implementing drag and drop specialised functionalities, ...
Wait, what?
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KNIME is the open source low-code/no-code platform for democratising everything about data: from data engineering, through ML, all the way to deploying dashboards, web apps, API and scheduled execution.
Users can still add code in SQL, Python, R, JavaScript.. but it's not necessary for most use cases.
Highlights at KNIME..
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In 2023 I joined the KNIME Educators Alliance team, collaborating with professors teaching and researching with KNIME from different faculties.
I also started to travel again teaching codeless prompt engineering
for KNIME Business Hub custom chatbots and other LLMs use cases.
During 2022 I have been leading the Upskilling team, scouting components builders from the KNIME community of open source users,
presenting at external communities such as Data Science Dojo and Pydata
on how to develop new KNIME extensions in Python instead of Java.
During 2021 I have been writing on new concepts such as data apps , integrated deployment ,
MLOps and the data science life cycle .
while rolling out verified components in monthly releases .
Starting from 2020 I have been leading the verified components team at KNIME,
where data science functionalities were packaged via low-code to be easily adopted by KNIME users. I personally implemented drag-and-drop functionalities around AutoML,
XAI and specific industries use cases.
In 2019 I travelled mostly in the US and Europe to give workshops and talks about KNIME Analytics Platform and KNIME Server use cases.
I also deep dived into active learning and weak supervision .
In 2018 I joined the KNIME team as a Data Scientist in Berlin. My main focus was autoML
and guided analytics .
Before KNIME..
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Media
Certifications
KNIME Projects
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→ Articles..
→ Applications..
→ Blog Posts..
→ White Papers..
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eXplainable AI: Interpreting Machine Learning with XAI (KNIME Press
Guided Labeling: Human-in-the-Loop Label Generation (KNIME Press
→ Webinars..
→ Talks..
→ Workshops..
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AI Learnathon // Topics: LLMs, Retrieval Augmented Generation (RAG), chatbots // Forum // Press Release
Python Integration // Topics: develop low-code/no-code tools in Python
Pydata, (Berlin - EN) (2022-11-16 ) [Meetup ]
Data Science Dojo, (Online - EN) (2022-10-19 ) [Meetup ]
PyData, (London - EN) (2022-10-03 ) [Meetup ]
Data Science Learnathon // Topics: data prep, modelling, deployment
KNIME Pros Learnathon // Topics: sharing, open source, community
Guided Analytics Learnathon // Topics: autoML, data visualization, visual analytics.
Coding Projects
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streamlit_apps - experimenting data apps for marketing analytics research.Rivelo - visual analytics tool for machine learning explanations.partial_dependence - python package for machine learning visualization.
Publications
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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