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With Roberto Cadili (Data Scientist Evangelism, KNIME), Lada Rudnitckaia (Data Scientist Education, KNIME).
Thu, May 02, 2024 @ 06:00 PM   FREE   Venue, 134 W 29th St, 2nd Fl
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Learn how to enrich data analytics with GenAI without writing a line of code.

During this event, we will explore a fraud detection use case & we will exploit the multi-language capabilities of GenAI to automatically generate custom alert messages.

During this hands-on workshop you will get familiar with the free low-code tool KNIME Analytics Platform, techniques for fraud detection, & the use of GenAI via the KNIME AI Extension (Labs).

Completely new to KNIME? We've got you covered! We will start with an introduction to KNIME Analytics Platform, making it easy to follow along even for newbies!

Without any coding experience you will learn to:

Detect frauds in investment contracts visually & using statistical techniques
Prompt engineer an LLM via the OpenAI integration
Create a vector store from a corpus of different types of investment contracts (the knowledge base)
Build & deploy a data app to display email alerts & make it available to authenticated users on a web browser
Other KNIME AI integrations we will discuss include GPT4All, Hugging Face, Chroma, FAISS & more.
Please come prepared & bring your laptop with KNIME Analytics Platform & the KNIME AI Extension (Labs) already installed.
Please note if you want to join onsite, registration is mandatory.


6:00 PM - Doors open, Welcome

6:10 PM - 6:40 PM : Introduction to KNIME, Demo of KNIME Analytics Platform & Q&A

6:40 PM - 7:10 PM : Introduction to fraud detection techniques, LLMs & the KNIME AI Extension (Labs) & Q&A

7:10 PM - 8:40 PM : Enrich Data Analytics for Fraud Detection with GenAI. We'll open KNIME on our laptops & build a KNIME workflow!

8:40 PM - 9:00 PM: Networking & refreshments

Meet the speakers:

Roberto Cadili : Roberto is a data scientist on the Evangelism team at KNIME. During his BSc. in Economics, he developed a genuine interest in statistics & data analysis. At the University of Konstanz, he pursued a MSc. in Social & Economic Data Science where he studied different machine learning algorithms & deep learning architectures with an emphasis on NLP & Computer Vision. As editor for Low Code for Data Science, he is helping the KNIME community shape successful data science stories, tutorials, & best practices that are worth sharing.

Lada Rudnitckaia : Lada is a Data Scientist on the Education team at KNIME & holds a master's degree in Data Science. She specialises in developing & teaching courses on data science & engineering with KNIME & is interested in explainable & responsible AI, machine learning models deployment, & data engineering.

Onsite Address:
134 W 29th St, New York, NY 10001, USA,
Floor 2
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