From the course: AI Data Strategy: Data Procurement and Storage
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Leveraging APIs for AI
From the course: AI Data Strategy: Data Procurement and Storage
Leveraging APIs for AI
- [Instructor] In this video, I'll be talking about leveraging APIs for sourcing data for AI product development. While open data platforms offer valuable resources, many companies need more dynamic real-time data access. Think of APIs as direct pipelines to data. Instead of downloading static datasets, you get fresh information exactly when you need it. But like any business decision, choosing the right API requires careful evaluation. The market offers three main ways to access data through APIs. First, standard APIs. These are for simple, regular data requests. Think of a retail store getting daily sales figures or a news app fetching hourly headlines. Next, flexible query APIs. These let you request the exact data you need. They're useful when different users need different information, like in a financial dashboard with varying detail levels. Lastly, there are real-time APIs. These provide constant data updates and are essential when every second counts, like, for example, when…
Contents
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Sourcing structured data for ML-driven AI products6m 50s
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Best practices for sourcing unstructured data4m 32s
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Understanding bias in traditional ML systems6m 42s
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Bias in generative AI: Challenges and mitigation strategies6m 19s
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Framework for bias mitigation in AI4m 2s
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Building intelligent systems with data protection5m 13s
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Open data platforms: Democratizing AI development5m 1s
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Leveraging APIs for AI6m 45s
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Building sustainable data ecosystems5m 3s
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