Data Labeling Strategies
Effective data labeling is crucial for building robust models, with options ranging from manual labeling to leveraging AI tools like GPT-4. Once a model is in production, implementing efficient serving strategies, such as dynamic batching and job scheduling, ensures optimal performance and continuous improvement. The flexibility of the Elixir and Erlang ecosystem offers numerous solutions for managing deployment challenges.In this clip
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Software Engineering Radio - the podcast for professional software developers
SE Radio 594: Sean Moriarity on Deep Learning with Elixir and Axon
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