I've added a. quick intro to ggfx for those curious about how to use it https://t.co/PNegGjQy9I
— Thomas Lin Pedersen (@thomasp85) February 24, 2021
I've added a. quick intro to ggfx for those curious about how to use it https://t.co/PNegGjQy9I
— Thomas Lin Pedersen (@thomasp85) February 24, 2021
Want to use Hugo for your website but hate that you can’t get the themes to look *exactly* how you want them? Check out my new blog post: Hugo for Fussy People! In it I go through how to turn a blank theme into precisely what you want. Fuss away!https://t.co/hEGZA7rgoH
— Dr. Jacqueline Nolis (@skyetetra) February 22, 2021
.@GradioML is a neat library for interacting with a trained model. It's useful for debugging and for giving collaborators the an easy way to interact with the model.
— Anthony Goldbloom (@antgoldbloom) February 21, 2021
Here's a notebook to try it:https://t.co/cwzzdpCTbZ
(Hit "Copy and Edit" and then run the notebook.) pic.twitter.com/FsVKULbLaV
Ray is an open-source library for parallel and distributed Python. It can be paired with #PyTorch to rapidly scale machine learning applications. Learn more below: https://t.co/UhfPxSEoWm
— PyTorch (@PyTorch) February 19, 2021
New in the scikit-learn main branch: a short tutorial on assessing and tuning quantile regression models with the new pinball loss metric:https://t.co/V3naQcxwz6
— Olivier Grisel (@ogrisel) February 19, 2021
before and after hyper-parameter tuning on data with asymmetric, heteroscedastic noise: pic.twitter.com/jVoPfENlxp
New code walkthrough on https://t.co/m6mT8Sa9M5: Switch Transformers, an architecture the makes it possible to increase the representational capacity of a Transformer while keeping its computational cost low. Implemented by Khalid Salamahttps://t.co/nkMu0QwPuo
— François Chollet (@fchollet) February 17, 2021
I am going to start my first lecture of my #DataScience collab software dev course with a watch party of this talk on RMarkdown Driven Development by @EmilyRiederer because I think it is such a narrative on how analysis code can evolve into packages:https://t.co/YZDtUFJyKg
— Tiffany Timbers (@TiffanyTimbers) February 17, 2021
For folks trying to get their head around PEP 634 (pattern matching), which will land in the next alpha release of 3.10, here's a brief tutorial I wrote: (more concise than the introduction in PEP 636): https://t.co/xWK2v0Rzgt
— Guido van Rossum (@gvanrossum) February 15, 2021
How to optimize @huggingface models with @weights_biases https://t.co/fmeaziPIFe
— Pete Skomoroch (@peteskomoroch) February 9, 2021
If you're interested in relation extraction & building NLP pipelines for custom use cases, check out this in-depth video tutorial by @Oxykodit 👇
— Ines Montani 〰️ (@_inesmontani) February 8, 2021
Bonus: a really cool illustrated breakdown of the ML model implementation & how to go from problem definition ➡️ model architecture. https://t.co/00lR46wEDI
Just finished a complete tutorial on optimizing @huggingface models with @weights_biases
— Boris Dayma (@borisdayma) February 4, 2021
No extra line of code required 🥳https://t.co/aMyQ6EQyJS
Running ML models in less than 100KB on embedded devices. By Pete Warden. https://t.co/cOXXu6R2kG pic.twitter.com/0yf2Ltmfcd
— Reza Zadeh (@Reza_Zadeh) February 4, 2021