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Tag: ml-ops

Testing Natural Language Models

The Data Exchange Podcast: Marco Ribeiro on why accuracy on benchmarks is not sufficient for evaluating NLP models.

ml-ops, nlp

What is AI Assurance?

The Data Exchange Podcast: Ofer Razon on building machine learning tools to scale AI operations.

infrastructure, ml-ops, risk, transcript

Democratizing Machine Learning

The Data Exchange Podcast: Ameet Talwalkar on the Determined Training Platform, Neural Architecture Search, Federated Learning and more.

infrastructure, ml-ops
Green Roof, California Academy of Sciences

How deep learning is being used in search and information retrieval

The Data Exchange Podcast: Edo Liberty on building tools for deploying deep learning models in search and information retrieval.

infrastructure, ml-ops, transcript, vectordb

The responsible development, deployment and operation of machine learning systems

The Data Exchange Podcast: Alejandro Saucedo on explainability, MLOps, adversarial robustness, and privacy.

ethics, infrastructure, ml-ops, risk

The evolution of TensorFlow and of machine learning infrastructure

The Data Exchange Podcast: Rajat Monga on TensorFlow 2.0, TFX, and the state of machine learning platforms.

distributed, hardware, infrastructure, ml-ops, open source, recommendations, tensorflow

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