Roger Frigola

@RogerFrigola

Machine Learning • Racing • Optimization. Formula 1, America's Cup and aerospace engineer. PhD . Flat sixes and four-cylinder transaxles [sic].

University of Cambridge
Vrijeme pridruživanja: srpanj 2013.

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  1. 16. lis 2019.
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  2. 13. lis 2019.

    "the marginal likelihood measures how well previous chunks of data predict future ones." , : This is an interesting way to see it. Is it an old insight?

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  3. 21. ruj 2019.
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  4. proslijedio/la je Tweet

    You've seen Boat One. Now it's your chance to help create Boat Two. 🛠️💪

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  5. 3. srp 2019.

    Mike Jordan on markets to define cost functions for AI : "Ignoring market mechanisms in developing modern societal-scale information-technology systems is like trying to develop a field of civil engineering while ignoring gravity."

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  6. 23. tra 2019.

    I'm wondering what's a typical weight sensitivity (in seconds/lap/kg) of a modern road-legal sports car on a racetrack. do you have any numbers on this?

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  7. 16. tra 2019.

    Porsche plans to hire 100 Artificial Intelligence experts in the near future. Nice!

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  8. 24. stu 2018.

    The "Big Data" buzzword has faded and is being replaced by "AI". They can be combined though, e.g. "I'll send you my Big Data in an Excel spreadsheet so that you can apply linear regression AI to discover new insights."

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  9. 16. lis 2018.

    That's quite funny. However, my feeling is that when people actually look at the data, as P(C)→0 then P(H|X) becomes proportional to P(X|H).

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  10. 11. lis 2018.

    Today I have used Taylor series expansions in two different occasions while working on an engineering problem. Almost everything we learnt in first year engineering maths has been useful to me at some point!

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  11. 28. ruj 2018.

    Totally agree. Sometimes each data point costs a lot of time/money to obtain and generalization is required using only a few hundreds of points. Gaussian processes are incredibly powerful in this regime.

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  12. 9. ruj 2018.

    Interesting article about some of the pitfalls of applying Machine Learning in practice. Agree on the need for "analytics translators": people who can simultaneously understand well the business problem and have an in-depth knowledge of Machine Learning.

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  13. 6. ruj 2018.

    Very interesting for any data-minded person or organization!

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    4. ruj 2018.

    The main conference sold out in 11 minutes 38 seconds

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  15. 9. kol 2018.
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  16. 6. srp 2018.

    Preparing for the big changes brought by Machine Learning and Artificial Intelligence.

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  17. 3. srp 2018.

    Learning to follow lanes by trial and error in 20 minutes using a single monocular camera.

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  18. 29. lip 2018.

    Awesome work by the Porsche LMP1 Team in destroying the 35 year old record of the Nordschleife!

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  19. 10. lip 2018.

    Amazing racing one year ago in the America's Cup Challenger Finals. What a finish!

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