Research to Production
The transition from research to deployed machine learning models presents significant challenges, particularly in determining which innovative ideas will perform well in real-world scenarios. Sharing knowledge and case studies is crucial for the community, as it enhances productivity and fosters learning from both successes and failures. Engaging in open discussions can lead to better practices and improved outcomes for everyone involved.In this clip
From this podcast
Gradient Dissent - A Machine Learning Podcast
Nimrod Shabtay — Deployment and Monitoring at Nanit
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