From the course: Data Science Foundations: Fundamentals
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Open data
From the course: Data Science Foundations: Fundamentals
Open data
- [Instructor] I love my public library here in Salt Lake City. And this right here is the main library downtown. It's a beautiful building. Has desks by a wall of windows looking out over the Wasatch Mountains. It's a great place to be, but even more, I love it because it's a library, and they have books there. They have a collection of over half a million books and other resources, including rows and rows of beautiful books on architecture and landscaping that I can never purchase on my own. I love to browse the shelves, find something unexpected and beautiful, go by the windows and enjoy it. Open data is like the public library of data science. It's where you can get beautiful things that you might not be able to gather or process on your own, and it's all for the public benefit. Basically, it's data that is free because it has no cost, and it's free to use, that you can integrate it into your projects and do…
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Contents
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Data preparation5m 26s
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(Locked)
Labeling data8m 48s
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(Locked)
In-house data5m 38s
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(Locked)
Open data4m 15s
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(Locked)
APIs2m 40s
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(Locked)
Scraping data4m 44s
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(Locked)
Creating data5m 36s
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(Locked)
Passive collection of training data3m 57s
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(Locked)
Self-generated data3m 30s
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(Locked)
Data vendors5m 30s
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(Locked)
Data ethics5m 14s
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