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Why Data is critical to being a successful AI/ML Product Manager by Amritha Arun Babu Mysore

AI is transforming industries, but what makes an AI product truly successful? Amrita, a product management expert, says that data is often overlooked, but it’s a key ingredient in any AI/ML product. Data fuels the entire ML lifecycle, from defining problems to training models. Understanding data is essential for AI/ML product managers, even if they aren’t data scientists. But AI products are complex, requiring collaboration between various stakeholders. Effective product managers bridge the gap, ensuring everyone works towards an ethical and unbiased product.

As AI becomes more integrated, it’s important to make sure that models are fair. Product managers can play a key role in establishing best practices to mitigate bias.

Building an AI product is an ongoing process. Monitoring and improvement are crucial. Amritha shares different approaches depending on the development stage. Data is the unsung hero of the story, and the product manager is the one who uses it to create a better future.

Watch the video.

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Bitol is a Linux Foundation AI & Data Sandbox project. As of now, it defines an open standard for data contracts called Open Data Contract Standard.

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