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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Collaborative workflows : Dataset storage and versioning tools should support collaborative workflows, allowing multiple users to access and contribute to datasets simultaneously, ensuring efficient collaboration among ML engineers, data scientists, and other stakeholders.

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Explainable AI (XAI): The Complete Guide (2024)

Viso.ai

The complexity of machine learning models has exponentially increased from linear regression to multi-layered neural networks, CNNs , transformers , etc. While neural networks have revolutionized the prediction power, they are also black-box models. Why do we need Explainable AI (XAI)?

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Google experts on practical paths to data-centricity in applied AI

Snorkel AI

RC : I have had ML engineers tell me, “You didn’t need to do feature selection anymore, and that you could just throw everything at the model and it will figure out what to keep and what to throw away.” That’s where you start to see data drift. So does that mean feature selection is no longer necessary?

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Google experts on practical paths to data-centricity in applied AI

Snorkel AI

RC : I have had ML engineers tell me, “You didn’t need to do feature selection anymore, and that you could just throw everything at the model and it will figure out what to keep and what to throw away.” That’s where you start to see data drift. So does that mean feature selection is no longer necessary?

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Google experts on practical paths to data-centricity in applied AI

Snorkel AI

RC : I have had ML engineers tell me, “You didn’t need to do feature selection anymore, and that you could just throw everything at the model and it will figure out what to keep and what to throw away.” That’s where you start to see data drift. So does that mean feature selection is no longer necessary?