Jean Cupe

@jcupe17

Paris, France
Vrijeme pridruživanja: siječanj 2018.
3 fotografije ili videozapisa Fotografije i videozapisi

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  1. proslijedio/la je Tweet
    29. sij

    Anemia affects 1.6 billion people globally, and diagnosis typically involves a blood test. Now research shows how machine learning can help detect the disease.

    9 replies 144 proslijeđena tweeta 549 korisnika označava da im se sviđa
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  2. proslijedio/la je Tweet
    30. sij

    The World Health Organization (WHO) has declared the coronavirus outbreak a global health emergency. Get the latest news and updates on the Wuhan outbreak below.

    115 proslijeđenih tweetova 168 korisnika označava da im se sviđa
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  3. proslijedio/la je Tweet
    22. sij

    Today, in collaboration with , we are releasing the “hemibrain” connectome, a detailed map of neuronal connectivity of roughly half of a fruit fly brain, plus tools for visualization and analysis. Learn more at .

    7 replies 163 proslijeđena tweeta 400 korisnika označava da im se sviđa
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  4. proslijedio/la je Tweet
    19. sij

    Here's a lecture by Andrew Trask () on privacy-preserving AI as part of the MIT Deep Learning lecture series. Preserving privacy boosts our ability to do science at a large-scale and to engineer intelligent systems that learn from data:

    10 replies 189 proslijeđenih tweetova 762 korisnika označavaju da im se sviđa
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  5. proslijedio/la je Tweet
    20. sij

    New tutorial!🚀 Intro to anomaly detection in images with and : - Automatically detect outliers/anomalies - Supervised and unsupervised training - Super easy to implement 👍

    5 replies 61 proslijeđeni tweet 199 korisnika označava da im se sviđa
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  6. proslijedio/la je Tweet
    21. sij

    Want six free chapters and YouTube screencasts of the new Lite for Microcontrollers TinyML book? Check out !

    6 replies 79 proslijeđenih tweetova 276 korisnika označava da im se sviđa
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  7. proslijedio/la je Tweet
    19. sij

    Health data are being generated and collected at an unprecedented scale, but whether big data will truly revolutionize healthcare is still a matter of much debate, according to a Review in .

    1 reply 35 proslijeđenih tweetova 60 korisnika označava da im se sviđa
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  8. proslijedio/la je Tweet
    18. sij

    In case you weren't yet convinced of the impact of deep learning in healthcare, has selected the deep learning for diabetic retinopathy detection paper (Gulshan et. al) as one of the 10 best papers published in JAMA in the last *decade*:

    88 proslijeđenih tweetova 265 korisnika označava da im se sviđa
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  9. proslijedio/la je Tweet
    18. sij

    i just read this excellent paper from 2018: "Relational inductive biases, deep learning, and graph networks". extremely well written, very clear, excellent graphics, and with code. highly recommended! paper: code: :

    46 proslijeđenih tweetova 332 korisnika označavaju da im se sviđa
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  10. proslijedio/la je Tweet
    17. sij

    After a year of dev, I am *extremely* excited to share this step-by-step tutorial Goal: to be the *easiest* intro to preserving, Deep Learning It's in I hope you enjoy it

    28 replies 651 proslijeđeni tweet 1.947 korisnika označava da im se sviđa
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  11. proslijedio/la je Tweet
    16. sij

    I did a deep-dive into Pages, and found it's possible to create a *really* easy way to host your own blog: no code, no terminal, no template syntax. I made "fast_template" to pull this together, & a guide showing beginners how to get blogging

    401 proslijeđeni tweet 1.663 korisnika označavaju da im se sviđa
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  12. proslijedio/la je Tweet
    15. sij

    Differentiable Digital Signal Processing (DDSP)! Fusing classic interpretable DSP with neural networks. ⌨️ Blog: 🎵 Examples: ⏯ Colab: 💻 Code: 📝 Paper: 1/

    27 replies 455 proslijeđenih tweetova 1.505 korisnika označava da im se sviđa
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  13. proslijedio/la je Tweet
    16. sij

    Introducing Reformer, an efficiency optimized architecture, based on the Transformer model for language understanding, that can handle context windows of up to 1 million words, all on a single accelerator with only 16GB of memory. Read all about it ↓

    14 replies 474 proslijeđena tweeta 1.352 korisnika označavaju da im se sviđa
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  14. proslijedio/la je Tweet
    14. sij

    At medical imaging we often need to make a little data go a long way. One under-appreciated approach for this is self-supervised learning. It's almost magical! I've written a little overview to help you get started. Let me know if you try it :)

    27 replies 282 proslijeđena tweeta 1.131 korisnik označava da mu se sviđa
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  15. proslijedio/la je Tweet
    13. sij

    Amazing! This real working deep learning image classifier is running, for free, on , is written entirely in notebooks with ipywidgets, & deployed with Voila. 13 lines of code :) Try it here:

    15 replies 177 proslijeđenih tweetova 789 korisnika označava da im se sviđa
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  16. proslijedio/la je Tweet
    11. sij

    Just another 17 lines of code and this is now a complete DataBunch cleaner for image classification! Select from train/valid, choose a category, and delete or re-label images, sorted by loss (so images most likely to be wrong appear first). Everything refreshes automatically.

    78 proslijeđenih tweetova 453 korisnika označavaju da im se sviđa
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  17. proslijedio/la je Tweet
    11. sij

    In our forthcoming book & course, you'll learn how to build a real deep learning web app from scratch, including downloading images using Bing's API. You'll also learn what can go wrong! (h/t )

    130 proslijeđenih tweetova 799 korisnika označava da im se sviđa
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  18. proslijedio/la je Tweet
    9. sij

    Research at Facebook AI: the year 2019 in review. Papers, datasets, software tools, awards....

    6 replies 158 proslijeđenih tweetova 500 korisnika označava da im se sviđa
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  19. proslijedio/la je Tweet
    20. pro 2019.

    Facebook AI has released Libri-light, the largest open source data set for speech recognition to date. This new benchmark helps researchers pretrain acoustic models to understand speech, with few to no labeled examples.

    84 proslijeđena tweeta 264 korisnika označavaju da im se sviđa
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  20. proslijedio/la je Tweet
    20. pro 2019.

    ALBERT is a new, open-source architecture for natural language processing that achieves state-of-the-art performance on multiple benchmarks with ~30% fewer parameters than . Learn all about it below:

    10 replies 557 proslijeđenih tweetova 1.573 korisnika označavaju da im se sviđa
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