Today we’re joined by Pat Woowong, principal engineer in the applied machine intelligence group at The Home Depot.
We discuss a project that Pat recently presented at the Google Cloud Next conference which used machine learning to predict shelf-out scenarios within stores. We dig into the motivation for this system and how the team went about building it, including what type of models ended up working best, how they collected their data, their use of kubernetes to support future growth in the platform, and much more.
For the complete show notes, visit twimlai.com/talk/175.
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ML-Powered Language Learning at Duolingo with Burr Settles - #412
Bridging The Gap Between Machine Learning and the Life Sciences with Artur Yakimovich - #411
Understanding Cultural Style Trends with Computer Vision w/ Kavita Bala - #410
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3D Deep Learning with PyTorch 3D w/ Georgia Gkioxari - #408
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Beyond Accuracy: Behavioral Testing of NLP Models with Sameer Singh - #406
How Machine Learning Powers On-Demand Logistics at Doordash with Gary Ren - #405
Machine Learning as a Software Engineering Discipline with Dillon Erb - #404
AI and the Responsible Data Economy with Dawn Song - #403
Relational, Object-Centric Agents for Completing Simulated Household Tasks with Wilka Carvalho - #402
Model Explainability Forum - #401
What NLP Tells Us About COVID-19 and Mental Health with Johannes Eichstaedt - #400
Human-AI Collaboration for Creativity with Devi Parikh - #399
Neural Augmentation for Wireless Communication with Max Welling - #398
Quantum Machine Learning: The Next Frontier? with Iordanis Kerenidis - #397
ML and Epidemiology with Elaine Nsoesie - #396
Language (Technology) Is Power: Exploring the Inherent Complexity of NLP Systems with Hal Daumé III - #395
Graph ML Research at Twitter with Michael Bronstein - #394
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