Even Oldridge

@Even_Oldridge

Sr Applied Research Scientist on the team. Focused on deep learning for RecSys and tabular data.

Vancouver, British Columbia
Vrijeme pridruživanja: siječanj 2018.
9 fotografija ili videozapisa Fotografije i videozapisi

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  1. proslijedio/la je Tweet
    prije 23 sata

    I just published my first post on Medium "Is the future of Neural Networks Sparse?" . Enjoy!

    35 proslijeđenih tweetova 165 korisnika označava da im se sviđa
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  2. proslijedio/la je Tweet
    4. velj

    "How to do machine learning efficiently". There's so much to love about this wonderful article.

    251 proslijeđeni tweet 1.160 korisnika označava da im se sviđa
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  3. 31. sij

    If you're running xgboost, lgbm, or other forest based models in production you need to check out our new forest inference library. 40x faster predictions, cheaper than cpu and way less rack space.

    40x faster predictions for even the deepest random forests with FIL’s new sparse forest support -
    69 proslijeđenih tweetova 308 korisnika označava da im se sviđa
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  4. 30. sij

    Mark's team is doing amazing work. Come help shape the future of data science and learn a ton along the way.

    Passionate about algorithms, software engineering, , , s? My team is looking for smart, driven C++ data analytics software interns.
    Prikaži ovu nit
    2 proslijeđena tweeta 4 korisnika označavaju da im se sviđa
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  5. proslijedio/la je Tweet
    30. sij

    This is a seriously great group to work in - very impressive results, and very innovative

    Passionate about algorithms, software engineering, , , s? My team is looking for smart, driven C++ data analytics software interns.
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    6 proslijeđenih tweetova 28 korisnika označava da im se sviđa
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  6. proslijedio/la je Tweet
    24. sij

    Nice example from Chris Deotte using cuML to accelerate kNN by 600x in a Kaggle kernel:

    8 proslijeđenih tweetova 30 korisnika označava da im se sviđa
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  7. proslijedio/la je Tweet
    20. sij

    I've blogged about my go-to tool for prediction on tabular data, CatBoost, and its differentiable (neural network based) counterpart, NODE. Future blog posts on other tools to follow!

    6 proslijeđenih tweetova 33 korisnika označavaju da im se sviđa
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  8. 16. sij

    It was such a pleasure to talk with about my love of and my work at using for tabular deep learning and RecSys.

    Really excited to be finally releasing my interview w another family member, Sr. Applied Research Sci , from the team: We talk all about his journey, fastai & his work: Audio: Video:
    1 reply 4 proslijeđena tweeta 37 korisnika označava da im se sviđa
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  9. proslijedio/la je Tweet
    11. sij

    “Meet AdaMod: a new deep learning optimizer with memory” by Less Wright

    211 proslijeđenih tweetova 821 korisnik označava da mu se sviđa
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  10. proslijedio/la je Tweet
    6. sij

    This is neat 😊 ✅Train a model ✅Realize you want some functionality the framework doesn't provide ✅Define said functionality in your notebook ✅🥳🎉💃 (this is using v2)

    24 proslijeđena tweeta 235 korisnika označava da im se sviđa
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  11. proslijedio/la je Tweet
    4. sij

    This is one of the coolest things I've seen on in a long time. Write a bot that plays a game - and everyone's bots are constantly pitted against each other and assigned skill ratings. 🎮 Finally time to dust off AlphaGo for Kaggle 😄

    We’re excited to announce a beta-version of a brand-new type of ML competition called Simulations! Compete against a set of rules, rather than against an evaluation metric. 👀 Give it a try today 👉
    5 replies 51 proslijeđeni tweet 296 korisnika označava da im se sviđa
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  12. proslijedio/la je Tweet
    21. pro 2019.

    Evidence that GPUs can be used to accelerate deep recommender systems at inference time, great work and al!

    Learn how to achieve 13x speedup and 11x throughput vs CPU on Wide & Deep recommender model using Inference SDK in new blog.
    4 proslijeđena tweeta 19 korisnika označava da im se sviđa
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  13. proslijedio/la je Tweet
    17. pro 2019.

    Learn how to achieve 13x speedup and 11x throughput vs CPU on Wide & Deep recommender model using Inference SDK in new blog.

    40 proslijeđenih tweetova 141 korisnik označava da mu se sviđa
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  14. proslijedio/la je Tweet
    14. pro 2019.

    Vancouver artist & painter learns python to program a robotic painting arm, then learns machine learning techniques like classification & CycleGAN to train the robot to paint “good” paintings

    9 proslijeđenih tweetova 30 korisnika označava da im se sviđa
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  15. proslijedio/la je Tweet
    13. pro 2019.

    Check out NVDashboard which makes visualizing resource utilization easy when running and in JupyterLab.

    1 reply 68 proslijeđenih tweetova 174 korisnika označavaju da im se sviđa
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  16. 13. pro 2019.

    Very excited to share the amazing libraries with the Vancouver data science community. Hope to see you there!

    Mark your calendars! For our next /AI in production meetup, we will have from talk about on Jan 7! RSVP here:
    8 proslijeđenih tweetova 19 korisnika označava da im se sviđa
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  17. proslijedio/la je Tweet
    12. pro 2019.

    I invite all my research and academia friends to apply for the Kaggle Open Data Research grant! We’re giving away $2k-$5k grants to support *your* research project and share your data and work on our public data platform

    Applications open now! We've kicked off the Kaggle Open Data Research Grant to support academic researchers on Kaggle! 19 grants of $2k-$5k each. Application deadline: Jan 9th, 2020
    1 reply 5 proslijeđenih tweetova 18 korisnika označava da im se sviđa
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  18. proslijedio/la je Tweet
    12. pro 2019.

    A few of us are meeting up tomorrow for lunch to discuss recommender systems. RSVP in the Whova app (meetup called “recommendation systems” if you want to join.

    4 proslijeđena tweeta 10 korisnika označava da im se sviđa
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  19. proslijedio/la je Tweet
    11. pro 2019.

    Analyzing and Improving the Image Quality of StyleGAN pdf: abs: github:

    5 replies 83 proslijeđena tweeta 297 korisnika označava da im se sviđa
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  20. proslijedio/la je Tweet
    11. pro 2019.

    to all the people asking “who cares?” in the comment section of this video... i care! i want to work on diverse teams which hold a variety of backgrounds and perspectives.

    Thank you for talking about diversity and inclusion at I have found wonderful support and proud we sponsored all groups
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    1 reply 6 proslijeđenih tweetova 24 korisnika označavaju da im se sviđa
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