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Quanta Magazine (N/A)
Season 2020 • Episode 21 • How to Shrink Big Data
Quanta Magazine Season 2020, Episode 21: How to Shrink Big Data
Jelani Nelson, a computer scientist at the University of California, Berkeley, expands the theoretical possibilities for low-memory streaming algorithms. He’s discovered the best procedures for answering on-the-fly questions like “How many different users are there?” (known as the distinct elements problem) and “What are the trending search terms right now?” (the frequent items problem). Nelson’s algorithms often use a technique called sketching, which compresses big data sets into smaller components that can be stored using less memory and analyzed quickly. Watch Quanta Magazine Season 2020, Episode 21 How to Shrink Big Data in HD free online. Enjoy high-quality streaming of Quanta Magazine Season 2020, Episode 21 and share your thoughts in the comments below!
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