Dr. Ravi Patel

@DrRaviPatel

I 💖 PyTorch

The Milky Way
Vrijeme pridruživanja: siječanj 2019.

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  1. proslijedio/la je Tweet
    prije 13 sati
    Odgovor korisnicima

    I really enjoyed the "100 Days of SwiftUI" course (iOS). Gets you hooked on building/tinkering in a way that felt very familiar coming from fastai!

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  2. proslijedio/la je Tweet

    Our 2017 Ira Sohn pick: Palihapitiya went on to compare Tesla to where Apple was in 2007 when the iPhone was released. "What we do know is that the early traction of Tesla is tracking very close to Apple," he said. 👍🏽👊🏽💪🏽

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  3. proslijedio/la je Tweet
    prije 22 sata
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  4. proslijedio/la je Tweet
    13. sij

    I have finally completed my PyTorch sequence-to-sequence tutorials. The 6 notebooks implement 5 neural network architectures from 5 different papers. Feel free to check it out and submit any feedback as a GitHub issue and I will make any changes ASAP.

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  5. proslijedio/la je Tweet
    2. velj

    Tesla will hold a super fun AI party/hackathon at my house with the Tesla AI/autopilot team in about four weeks. Invitations going out soon.

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  6. proslijedio/la je Tweet
    31. sij

    THIS is the PETA ad the apparently didn’t want you to see and pressured to snub. It envisions a world where respect is the right of every being and pays homage to Kaepernick and movements rejecting injustice.

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  7. proslijedio/la je Tweet
    31. sij

    A full build of Autopilot neural networks involves 48 networks that take 70,000 GPU hours to train. Together, they output 1,000 distinct tensors (predictions) at each timestep. This is what a Tesla autopilot sees [source: ]

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  8. proslijedio/la je Tweet
    1. velj

    Check this out! There will be racing at NVIDIA GTC 2020 Jetson Developer Days. DIY Autonomous Car Racing with NVIDIA Jetson via

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  9. proslijedio/la je Tweet
    31. sij

    What unreleased FSD Autopilot sees. Straight from Tesla Autopilot recruiting website.

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  10. proslijedio/la je Tweet
    30. sij

    Facebook has taken down my Github repository about Instagram API: Here the DCMA notice: Reverse engineering should be a user right, we don’t know if apps are violating user privacy or backdooring our devices.

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  11. proslijedio/la je Tweet
    31. sij

    We are 46 days away from election day and 2 days away from our first debate. We are trying to raise $5,000 by midnight tonight. Chip in what you can and continue fueling our movement!! First 5 donors using this link will get a call directly from me!

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  12. proslijedio/la je Tweet
    31. sij

    Transformers 2.4.0 is out 🤗 - Training transformers from scratch is now supported - New models, including *FlauBERT*, Dutch BERT, *UmBERTo* - Revamped documentation - First multi-modal model, MMBT from , text & images Bye bye Python 2 🙃

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  13. proslijedio/la je Tweet
    30. sij

    What being a part of has taught me over the last 30 years is this: the magic of what we do at iRobot is that there is no magic... only a lot of hard work and decisions. What else has our quest to change the world taught us? Latest blog👇

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  14. proslijedio/la je Tweet
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  15. proslijedio/la je Tweet
    30. sij

    40x faster predictions for even the deepest random forests with FIL’s new sparse forest support -

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  16. proslijedio/la je Tweet
    29. sij

    Astros trashcan bangs by date. See all the data at .

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  17. proslijedio/la je Tweet
    Odgovor korisniku/ci

    Thanks! Please help me spread the word by writing a testimonial here:

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  18. proslijedio/la je Tweet
    29. sij

    Remarkable. Electronic patient records systems used by thousands of doctors were programmed to automatically suggest opioids at treatment, thanks to a secret deal between the software maker and a drug company. reports. via

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  19. proslijedio/la je Tweet
    29. sij

    🤔 Wondering why you keep hearing that unprotected left turns are an incredible engineering challenge for self-driving cars? Learn more by joining 10k others in subscribing to my free, pun-heavy email newsletter “Let Me Level 5 With You”. 👉

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  20. proslijedio/la je Tweet
    29. sij

    Most discoveries in finance are false due to p-hacking. This seminar explains how machine learning methods can overcome the flaws of p-values, and facilitate the discovery of new theories:

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