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Abstract It's 2024 but data curation for ML/AI is still incredibly hard. MLOps Community Meetup ! Two weeks ago, we talked to Modern data workloads come in all shapes and sizes - numbers, strings, JSONs, images, whole PDF textbooks and more. www.pydata.org Everyone who codes can save time by reusing configuration — whether for logging in to cloud providers or ... Speaker: Jan Lukány, ML/Data Engineer Team Lead at Datamole Jan is presenting an opinionated project template for ... View this you are an ML practitioner and want to learn how you can: * Crunch time-series and forecasting data at a massive scale ...
Martin Kleppmann is a researcher and the author of Designing Data-Intensive Applications, one of the most influential books on ...
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The Daft distributed Python data engine: multimodal data curation at any scale // Jay Chia // DE4AI
Python Power: How Daft Embeds Models and Revolutionizes Data Processing //Sammy Sidhu// Podcast #165
Dataframes Are All You Need: MLOps on Easy Mode // Jay Chia // MLOps Meetup #124
Building a Multimodal Data Lakehouse with the Daft Distributed Python Dataframe
Python for Data Engineers Full Course 2026 | Basics to Advanced
Let's build GPT: from scratch, in code, spelled out.
Jeff Hale - Supercharge your Python code with Blocks | PyData NYC 2022
🚀 Python Project Template – Jan Lukany, Datamole
TokioConf 2026 - Async Rust Meets Async Python: How Daft runs... by Colin Ho, Srinivas Lade
Do THIS Instead of Watching Endless Tutorials - How I'd Learn Python FAST (2025)
Ray NYC March 2023 with NYC ML/AI Meetup
Designing Data-intensive Applications with Martin Kleppmann
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Last Updated: June 14, 2026
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