Visualize - Bringing Structure to Unstructured Data // Markus Stoll // MLOps Podcast

Visualize - Bringing Structure to Unstructured Data // MLOps Podcast #258 with Markus Stoll, CTO of Renumics.

A huge thank you to ‪@SAS‬ for their generous support!

// Abstract
This talk is about how data visualization and embeddings can support you in understanding your machine-learning data. We explore methods to structure and visualize unstructured data like text, images, and audio for applications ranging from classification and detection to Retrieval-Augmented Generation. By using tools and techniques like UMAP to reduce data dimensions and visualization tools like Renumics Spotlight, we aim to make data analysis for ML easier. Whether you're dealing with interpretable features, metadata, or embeddings, we'll show you how to use them all together to uncover hidden patterns in multimodal data, evaluate the model performance for data subgroups, and find failure modes of your ML models.

// Bio
Markus Stoll began his career in the industry at Siemens Healthineers, developing software for the Heavy Ion Therapy Center in Heidelberg. He learned about software quality while developing a treatment machine weighing over 600 tons. He earned a Ph.D., focusing on combining biomechanical models with statistical models, through which he learned how challenging it is to bridge the gap between research and practical application in the healthcare domain. Since co-founding Renumics, he has been active in the field of AI for Engineering, e.g., AI for Computer Aided Engineering (CAE), implementing projects, contributing to their open-source library for data exploration for ML datasets (Renumics Spotlight) and writing articles about data visualization.

// MLOps Jobs board
https://mlops.pallet.xyz/jobs

// MLOps Swag/Merch
https://mlops-community.myshopify.com/

// Related Links
Website: https://renumics.com/
MLSecOps Community: https://community.mlsecops.com/
Blogs: https://towardsdatascience.com/visual...
:   / how-to-explore-and-visualize-ml-data-for-o...  

-------------- ✌️Connect With Us ✌️ ------------
Join our slack community: https://go.mlops.community/slack
Follow us on Twitter: @mlopscommunity
Sign up for the next meetup: https://go.mlops.community/register
Catch all episodes, blogs, newsletters, and more: https://mlops.community/

Connect with Demetrios on LinkedIn:   / dpbrinkm  
Connect with Markus on LinkedIn:   / markus-stoll-b39a42138  

Timestamps:
[00:00] Markus' preferred coffee
[00:15] Takeaways
[01:41] Please like, share, leave a review, and subscribe to our MLOps channels!
[01:50] Register for the Data Engineering for AI/ML Conference now!
[02:27] Current focus and updates
[04:43] 3D Embeddings Visualization Explained
[07:07] Question Embeddings vs Retrieval
[08:24] Using heat maps effectively
[10:30] User insights visualization RAG
[16:59] 3D Crash Simulation Analysis
[20:33] Simulation purpose clarification
[22:34] Evaluating test data use cases
[24:22] Real-world car testing
[29:48] Identifying data issues early
[33:33] Multimodal data integration
[37:42] Custom vs Fine-tuned models
[39:45] Data processing challenges
[45:58] Use case-driven MVP
[48:26 - 50:08] SAS Ad
[50:09] Wrap up