From the course: AI Data Strategy: Data Procurement and Storage
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Open data platforms: Democratizing AI development
From the course: AI Data Strategy: Data Procurement and Storage
Open data platforms: Democratizing AI development
- [Instructor] So far we covered how to build a data procurement strategy, now let's explore a specific procurement option that's become increasingly important, open data platforms. These platforms can dramatically reduce your data costs, but only if you use them wisely. Let's take a look at how to go about doing that. When you're working on an AI project, sourcing data doesn't always mean starting from scratch. Open data platforms provide an incredible opportunity to access high quality data sets that are ready to use. These platforms can save you time, reduce costs, and help you focus on building your model instead of spending weeks or months collecting and cleaning data. One of the biggest advantages of open data platforms is that they provide more than just raw data. Platforms like Google Dataset Search include metadata, information about the data, such as what it contains, how it was collected, and the licensing terms. This helps you quickly decide if a dataset fits your…
Contents
- (Locked)Sourcing structured data for ML-driven AI products6m 50s
- (Locked)Best practices for sourcing unstructured data4m 32s
- (Locked)Understanding bias in traditional ML systems6m 42s
- Bias in generative AI: Challenges and mitigation strategies6m 19s
- (Locked)Framework for bias mitigation in AI4m 2s
- (Locked)Building intelligent systems with data protection5m 13s
- (Locked)Open data platforms: Democratizing AI development5m 1s
- (Locked)Leveraging APIs for AI6m 45s
- (Locked)Building sustainable data ecosystems5m 3s
- (Locked)