Fireside Chat on Experimentation in ML with TWIML's Sam Charrington [AUDIO ONLY]
Experimentation is foundational to model development, whether in the context of artificial intelligence, high performance computing or everything in between. We design, explore, iterate, adjust, evolve, improve, optimize and scale our experiments to better understand our models. But there are many moving parts of this experimental process and putting all of them together can be time-consuming and, at times, tough to get right. Is there a combination of techniques and tools that can make this messy process easier?
Tune into this fireside chat to hear Sam Charrington from TWIML and Scott Clark from SigOpt debate this very question — sharing their own experiences running into dead ends and uncovering novel insights through experimentation.
Originally recorded Wednesday, May 18, 2022.
✔️ Learn more about SigOpt: https://sigopt.com
✔️ Learn more about TWIML: https://twimlai.com
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