Miles Turpin

@milesaturpin

Undergrad . Interested in machine learning research and Effective Altruism. Aspiring abstract aesthete.

Vrijeme pridruživanja: svibanj 2017.

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  1. 26. sij
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  2. 26. sij

    4:12 No thing other than the posterior over models is more acceptable to God, and escheweth evil?

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  3. 26. sij

    30:23 Then said Elkanah her husband liveth; but only if the mode is a Gaussian prior.

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  4. 26. sij

    7:15 Beware of the parameters.

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  5. 26. sij

    Carefully evaluating precise gradients using large datasets is often better than a strong hand, hath the LORD brought forth into their mind.

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  6. 26. sij

    47:13 And he said unto thy neighbour, do the gradient descent.

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  7. 26. sij

    Jesus of the Hebrews that were added to the LORD, he is gracious and merciful, slow to overfit, as is the value of λ.

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  8. 26. sij

    He said unto them, Have ye suffered so many equations?

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  9. 26. sij

    21:17 And David said to the Lord GOD; less data, is best.

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  10. 26. sij

    I present Love Thy Nearest Neighbor: a Markov chain generator trained on the King James Bible and Kevin Murphy’s Machine Learning: A Probabilistic Perspective. Behold...

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  11. 4. sij

    It took me 20 minutes to fall in love with

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  12. 28. pro 2019.
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  13. 28. pro 2019.

    The answer depends on what kind of future data you wish to generalize to. If you want to generalize to new time points for a given patient, then you have tons of data! But if you want to generalize to new patients… then n=5. 2/2

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  14. 28. pro 2019.

    A deceptively difficult question: how much data do I have? If your data is hierarchical the answer is not obvious. Say I have a dataset of 5 patients, and for each one, fine-grained measurements across 1 million time points. Is my sample size 5 or 5 million? 1/2

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  15. proslijedio/la je Tweet
    23. pro 2019.

    Just sent a Momentum gift card (). A fun way to introduce friends/family to effective giving!

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  16. proslijedio/la je Tweet

    We’ve made the decision to stop all political advertising on Twitter globally. We believe political message reach should be earned, not bought. Why? A few reasons…🧵

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  17. proslijedio/la je Tweet
    10. ruj 2019.
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    This abstractive summarization paper abstract is a real roller coaster!

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  18. proslijedio/la je Tweet
    7. ruj 2019.

    Over the years, I've watched conditional renormalization grow from a style transfer hack to a key mechanism in recent results; in this post I chart out how the idea evolved from humble beginnings into a flexible and important technique

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  19. proslijedio/la je Tweet
    13. kol 2019.

    I made a Markov chain text generator and trained it on the concatenated text of the King James Bible and & Chuang's canonical quantum information book (the quantum bible). Some of the finer pearls of wisdom I found:

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  20. proslijedio/la je Tweet
    8. srp 2019.
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