Jan. 16, 2024, 3 p.m. | H2O.ai

H2O.ai www.youtube.com

Welcome back! In this session, we'll dive into the outcomes of your completed experiment. We'll explore how the model is assessed, understand the significance of higher mAP scores for superior performance, and review the default hyperparameters applied during the experiment execution.

🔍 Explore more content in our H2O Hydrogen Torch Starter Course Playlist by visiting: https://youtube.com/playlist?list=PLNtMya54qvOHVk8z5V1ccO33AZKNn77VI&si=5rp0mnKH9xTwlhFn

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experiment explore h2o hydrogen map path performance review session significance torch

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US