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perturbation

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Sun, Sep 01, 2013, 9:18 PM UTC
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About perturbation

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  1. comment
    Comment #48405261

    Location: Dallas / Fort Worth, TX, USA Remote: Yes Willing to relocate: No Technologies: PyTorch, Tensorflow 2 / Keras, Rust, Go, Python. Model training, deployment, LLMs/SLMs. Doc…

  2. comment
    Comment #42132254

    I think a lot of these may have improved since your last experience with Keras. It's pretty easy to override the training loop and/or make custom loss. The below is for overriding …

  3. comment
    Comment #33840634

    The big thing that PyTorch Mobile is lacking compared to TF Lite is on-device accelerator support (GPU/DSP/etc.) (there's experimental support for NNAPI https://pytorch.org/tutoria…

  4. comment
    Comment #26121727

    Let's hope not, I like autodiff (and this project :( ).

  5. comment
    Comment #23690403

    > To return to the point about image augmentations being hard to add: It's so easy to explain what your training code should do "Just distort the hue a bit" and there seem to be op…

  6. comment
    Comment #22576874

    If you don't mind getting your hands dirty a bit, I think Nvidia's model [Jasper]( https://arxiv.org/pdf/1904.03288.pdf ) is near SOTA, and they have [pretrained models]( https://n…

  7. comment
    Comment #22109182

    This is cool - might be worth training a simple discriminator model to identify your utterances, and then you can use the plug-and-play language model (PPLM - https://github.com/hu…

  8. comment
    Comment #21885766

    Ah, thank you for explaining! That makes sense.

  9. comment
    Comment #21885611

    Additionally, the Nim code was not compiled with many optimizations turned on! (I.e., without -d:release). $ nim c -o:base64_test_nim -d:danger --cc:gcc --verbosity:0 base64_test.n…

  10. comment
    Comment #21885588

    Another thing I noticed: the Nim code was compiled without the -d:release flag. For example, the JSON test was compiled with: $ nim c -o:json_test_nim -d:danger --cc:gcc --verbosit…

  11. comment
    Comment #21182299

    I'd recommend Elements of Statistical Learning or ISLR instead, if you want to start with a theory-heavy introduction. Most of what you need for DS you'd I think better learn throu…

  12. comment
    Comment #21053318

    Congrats guys!!! This has been much-anticipated and I'm very excited. I personally wish that the owned reference stuff ( https://nim-lang.org/araq/ownedrefs.html ) had been part of…

  13. comment
    Comment #19790410

    > * They measure the wrong things that reward the network. Because the dataset is imbalanced you can't use an ROC curve, sensitivity, or specificity. You need to use precision and …

  14. comment
    Comment #19735667

    https://github.com/yuki24/did_you_mean#installation : Ruby 2.3 and later ships with this gem and it will automatically be required when a Ruby process starts up. No special setup i…

  15. comment
    Comment #19627878

    AutoML is essentially training a ML model using some heuristics or optimization algorithm to select model architecture and train a model. Feature engineering / feature synthesis as…

  16. comment
    Comment #19492677

    Disclaimer: I really love Nim and have written a fair amount in it, but I'm not a language designer guy. I like that this will make multithreading easier with shared memory, but I …

  17. comment
    Comment #19290526

    Are you using reticulate ( https://github.com/rstudio/reticulate ), or having Python spawn a new worker process for R?

  18. comment
    Comment #19289915

    Location: Dallas, TX Remote: Yes Technologies: Keras, R, Python, and Spark are what I use ever day. Jupyter, scikit-learn, spaCy, NLTK, H2O, mlr, caret, prophet, tsfresh, ggplot, a…

  19. comment
    Comment #19284673

    Dplyr works great with SQL (both SQLite and others).

  20. comment
    Comment #19282989

    Their example with LightGBM ( https://nni.readthedocs.io/en/latest/gbdt_example.html ) is very cool - I wanted to put together a custom script with mlflow + catboost + mlrMBO to do…

  21. comment
    Comment #19173272

    Haven't looked at MyCroft before. It looks like MyCroft exposes less of the nuts-and-bolts of modeling? I'm not sure where I would plug in a custom entity extraction or intent dete…

  22. comment
    Comment #19171775

    I'll +1 SNIPs or Rasa, they're both really nice. It looks like the NLU part of Leon is a logistic regression classifier ( https://github.com/leon-ai/leon/blob/360d1020c4bd8bf1df376…

  23. comment
    Comment #19164288

    I think they want data scientist to do plain-old-data-engineer work, but not just plain-old-data-engineer work. Getting / cleaning data is part of the job description, IMHO. You ca…

  24. comment
    Comment #19164243

    I have been a data scientist for the last 4 years. I think (one of) the problems with the data science career field is that there are a lot of juniors who want to run sklearn and c…

  25. comment
    Comment #18981061

    To some extent, R works like this... packages are only on CRAN if they pass automatic checks and there's a pretty strong culture of testing with testthat. You can have your own pac…