From the course: Data Science Foundations: Fundamentals
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Prescriptive analytics
From the course: Data Science Foundations: Fundamentals
Prescriptive analytics
- [Instructor] Sometimes you just have to do the impossible. About 2,500 years ago, the Greek philosopher Zeno of Elea argued that it was impossible to get from point A to point B, like walking across your room. His reasoning was that before you could get all the way to point B, you first had to get halfway there. And before you could get the rest of the way, you had to go halfway again. The process of getting halfway would occur an infinite number of times, which Zeno said was impossible, so you could never get to point B. Now, aside from the fact that Zeno didn't know that you could solve an infinite series problem with calculus, the obvious answer is that people walk from one part of the room to the other all the time. So the theoretically impossible task was obviously possible and accomplished frequently. And that gets us to an interesting issue about cause and effect relationships. Now, strictly speaking, three things need to happen to be able to say that one thing causes…
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Contents
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Artificial intelligence10m 56s
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Machine learning8m 6s
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Deep learning and neural networks8m 22s
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Transformers and attention for generative AI4m 58s
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Big data5m 36s
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Predictive analytics5m 46s
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Prescriptive analytics8m 58s
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The evolution of business intelligence5m 6s
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