MLOps.community
A podcast by Demetrios
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Categories:
401 Episodes
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MLOps at the Crossroads // Patrick Barker & Farhood Etaati // #204
Published: 1/16/2024 -
Pioneering AI Models for Regional Languages // Aleksa Gordić // #203
Published: 1/12/2024 -
Small Data, Big Impact: The Story Behind DuckDB // Hannes Mühleisen & Jordan Tigani // #202
Published: 1/9/2024 -
Language, Graphs, and AI in Industry // Paco Nathan // #201
Published: 1/5/2024 -
Founding, Funding, and the Future of MLOps // Mihail Eric // #200
Published: 1/2/2024 -
Challenges Operationalizing ML (And Some Solutions) // Nathan Ryan Frank // #199
Published: 12/29/2023 -
Inferring Creativity // Nick Hasty // #198
Published: 12/26/2023 -
The Role of Infrastructure in ML // Niels Bantilan // #197
Published: 12/22/2023 -
LLMs in Focus: From One-Size Fits All to Verticalized Solutions // Venky Ganti & Laurel Orr // #196
Published: 12/19/2023 -
[Exclusive] Weights & Biases Round-table // Model Management in a Regulated Environment
Published: 12/15/2023 -
Building the Future of AI in Software Development // Varun Mohan // #195
Published: 12/12/2023 -
AI in Education Fireside Chat // LLMs in Production Conference 3
Published: 12/8/2023 -
[Exclusive] Tecton Round-table // Get your ML Application Into Production
Published: 12/7/2023 -
DSPy: Transforming Language Model Calls into Smart Pipelines // Omar Khattab // #194
Published: 12/5/2023 -
Fireside Chat with LLM Startups // LLMs in Production Conference 3
Published: 12/1/2023 -
LLMs in Biomaterials Production // Pierre Salvy // #193
Published: 11/28/2023 -
Product Engineering for LLMs // LLMs in Production Conference Part III // Panel 2
Published: 11/24/2023 -
Enterprises Using MLOps, the Changing LLM Landscape, MLOps Pipelines // Chris Van Pelt // #192
Published: 11/21/2023 -
Building Defensible AI Apps // Gregory Kamradt // #191
Published: 11/17/2023 -
Guarding LLM and NLP APIs: A Trailblazing Odyssey for Enhanced Security // Ads Dawson // #190
Published: 11/14/2023
Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations.