Piero Ferrante

@the_real_pdf

Principal Data Scientist | Advisor |

New York, NY
Vrijeme pridruživanja: veljača 2009.
3 fotografije ili videozapisa Fotografije i videozapisi

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  1. proslijedio/la je Tweet
    24. sij

    I have just released versions 0.9.1 and 0.10.0 of seaborn, a Python library for data visualization. The new versions contain a number of improvements, and version 0.10.0 drops support for Python 2. Check out the release notes for more information:

    105 proslijeđenih tweetova 457 korisnika označava da im se sviđa
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  2. proslijedio/la je Tweet
    24. sij

    Introducing scikit-geometry, a Python library with useful geometric types and functions for and :

    8 replies 197 proslijeđenih tweetova 608 korisnika označava da im se sviđa
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  3. proslijedio/la je Tweet
    13. pro 2019.

    🐼🤹‍♂️ pandas trick #96: Want to create interactive plots using pandas 0.25? 📊 1. Pick one: ➡️ pip install hvplot ➡️ conda install -c conda-forge hvplot 2. pd.options.plotting.backend = 'hvplot' 3. df.plot(...) 4. 🥳 See example 👇

    8 replies 196 proslijeđenih tweetova 709 korisnika označava da im se sviđa
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  4. proslijedio/la je Tweet
    12. pro 2019.

    Excited to announce that the 3rd ed of Python Machine Learning is now finally available! What's new? In a nutshell: Ch1-12 upd for sklearn 0.22; Ch 13-16 upd. for TensorFlow 2. And most excitingly: 2 new chapters (17&18) -> GANs and Reinforcement Learning!

    15 replies 132 proslijeđena tweeta 578 korisnika označava da im se sviđa
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  5. proslijedio/la je Tweet
    11. pro 2019.

    Altair 4.0 is released! Try it with: pip install -U altair The full list of changes is at ...read on for some highlights.

    15 replies 305 proslijeđenih tweetova 964 korisnika označavaju da im se sviđa
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  6. proslijedio/la je Tweet
    7. pro 2019.

    Given I've spent many years actually writing many popular C-extensions for Python, please take note of this strong recommendation!

    “Instead of writing C extensions, I strongly encourage folks to use one of these other tools...” at Austin keynote
    5 replies 64 proslijeđena tweeta 221 korisnik označava da mu se sviđa
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  7. proslijedio/la je Tweet
    3. pro 2019.

    Scikit-learn 0.22 is out! New website, new plotting API, permutation variable importances, support for missing values in GBRT, KNN Imputer, Decision Tree pruning and much more. Highlights: Full changelog:

    We just released the final 0.22, and you can start using it: `pip install -U scikit-learn` ✨ Check out for a short list of highlights.
    102 proslijeđena tweeta 278 korisnika označava da im se sviđa
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  8. proslijedio/la je Tweet
    2. pro 2019.

    My talk on Scalable Machine Learning with from PyData NYC is now online: Slides are at

    1 reply 42 proslijeđena tweeta 182 korisnika označavaju da im se sviđa
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  9. proslijedio/la je Tweet
    21. stu 2019.

    IMHO, technical debt is not discussed enough in the context of scientific methods, especially computational ones. Accumulating complexity over time leads to diminishing returns with super-linear costs. We need to always simplify our scientific pipelines.

    6 replies 46 proslijeđenih tweetova 140 korisnika označava da im se sviđa
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  10. proslijedio/la je Tweet
    8. stu 2019.

    Time series prediction is clearly a very important problem for . Here is a blogpost and a couple of papers from their presentation at :

    170 proslijeđenih tweetova 656 korisnika označava da im se sviđa
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  11. proslijedio/la je Tweet
    30. lis 2019.

    A way to describe intelligence is that it is the power to produce abstraction. AI in the true sense would be Autonomous Abstraction. Current AI consists of recording abstractions generated by the human mind (via hard-coding rules, training ML models on human-labeled data, etc).

    30 replies 210 proslijeđenih tweetova 645 korisnika označava da im se sviđa
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  12. proslijedio/la je Tweet
    23. lis 2019.

    More people should know about xarray. Not everything in life is a 2D table, especially in the natural sciences. Xarray makes N-dimensional SciPy code easy and pretty.

    New post! Exploring using some of my old neuroscience data. It's pretty powerful! Would love to see this and other tools in the stack in the neuro community.
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    21 proslijeđeni tweet 85 korisnika označava da im se sviđa
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  13. proslijedio/la je Tweet
    1. lis 2019.

    We launched today! 🎈🥳 🚀Streamlit is the fastest way to build custom tools. $ pip install streamlit $ streamlit hello See more:

    20 replies 220 proslijeđenih tweetova 635 korisnika označava da im se sviđa
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  14. proslijedio/la je Tweet
    24. ruj 2019.

    If your classifier is "99% accurate", either you're using the wrong metric (a metric this high is not informative), or you have an overfitting or leakage problem. Metrics are feedback points on the way towards better models. Not trophies to show off. They should be actionable.

    56 replies 620 proslijeđenih tweetova 2.808 korisnika označava da im se sviđa
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  15. proslijedio/la je Tweet
    12. ruj 2019.

    Huh, just hearing about it for the first time, looks handy & convenient: "sktime -- A scikit-learn compatible Python toolbox for learning with time series data"

    80 proslijeđenih tweetova 327 korisnika označava da im se sviđa
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  16. proslijedio/la je Tweet
    27. kol 2019.

    Thinking more about survival function prediction, and a new Python project, 𝚕𝚒𝚏𝚎𝚕𝚒𝚔𝚎:

    5 replies 35 proslijeđenih tweetova 132 korisnika označavaju da im se sviđa
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  17. proslijedio/la je Tweet
    21. kol 2019.

    opendrop: Apple AirDrop Implementation Written in Python

    15 proslijeđenih tweetova 70 korisnika označava da im se sviđa
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  18. proslijedio/la je Tweet
    20. kol 2019.

    Excited to share our notebook curriculum for learning visualization! Visual encoding, data transformation, interaction, maps, & more! Into Python? Here's Altair + Jupyter: Prefer JavaScript? See Vega-Lite + :

    12 replies 543 proslijeđena tweeta 1.796 korisnika označava da im se sviđa
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  19. proslijedio/la je Tweet
    16. kol 2019.

    Speaker diarization—separating speech from different speakers—is critical for joint speech recognition. New research based on a recurrent neural network transducer architecture improves diarization performance by a factor of ~10. Learn how it's done here:

    9 replies 228 proslijeđenih tweetova 626 korisnika označava da im se sviđa
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  20. proslijedio/la je Tweet
    15. kol 2019.

    Very excited to announce Snorkel v0.9, the biggest update to our open source framework for programmatically labeling, transforming & structuring training datasets for . We add new core ops, algs, tutorials, and a full redesign of the core lib

    98 proslijeđenih tweetova 302 korisnika označavaju da im se sviđa
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