Introducing Danfo.js 👋
— TensorFlow (@TensorFlow) August 25, 2020
Danfo.js is a Pandas-like Library in #JavaScript that’s #MadeWithTFJS, and provides intuitive data structures for manipulating and processing structured data. Learn more in this article by @risingodegua and @steveoni.
Read now → https://t.co/dGKYZtCVu7 pic.twitter.com/DAZD3tkHkX
Want to learn how to deploy an R model and a Shiny app with GitHub Actions? My #rstatsnyc talk is available to watch now: https://t.co/deS68jU3T6 #rstats
— David Smith (@revodavid) August 25, 2020
torchcsprng is a PyTorch C++/CUDA extension that provides cryptographically secure pseudorandom number generators for PyTorch based on Salmon et. al's "Parallel Random Numbers". Learn more:https://t.co/OQMrk5Y77C
— PyTorch (@PyTorch) August 24, 2020
Sometimes it can be hard to get a sense for what is going on in code. This is especially true when the code was automatically generated from e.g. automatic differentiation. To help with this here's a little prototype of a library to convert from jax to latex.
— Sam Schoenholz (@sschoenholz) August 24, 2020
E.g. this code pic.twitter.com/Akc4776mD8
public-apis: A Collective List of Free APIs for Use in Software and Web Development https://t.co/y86vbMYYtJ
— PyCoder’s Weekly (@pycoders) August 20, 2020
Stochastic Weight Averaging (SWA) is a simple procedure that improves generalization in deep learning over Stochastic Gradient Descent (SGD). PyTorch 1.6 now includes SWA natively. Learn more from @Pavel_Izmailov, @andrewgwils and Vincent: https://t.co/1u5yRwfWXT
— PyTorch (@PyTorch) August 18, 2020
100x Faster Machine Learning Model Ensembling with @rapidsai cuML and Scikit-Learn Meta-Estimators by Nick Becker https://t.co/GDr3KvsAlS
— Bojan Tunguz (@tunguz) August 18, 2020
11 state-of-the-art sentence embedding models are now included in the Hugging Face hub, thanks to @UKPLab 🚀
— Hugging Face (@huggingface) August 17, 2020
The model hub (linked) shows how to use these models both with the authors' sentence-transformers library as well as with native 🤗 Transformers.https://t.co/h6ljxWPS7B pic.twitter.com/w81dZucv5L
A very simple Kaggle notebook that shows how to use KerasTuner to automatically find a high-performing model: https://t.co/LjXfpZJACw
— François Chollet (@fchollet) August 17, 2020
Includes finding the best image augmentation config as part of the parameter search (this is actually one of the most important things to tune) pic.twitter.com/pasgIGHVx5
Someone asked about converting #CSV to @ApacheParquet on the @RAPIDSai slack, and @rodaramburu of @blazingsql reminded us of this excellent blog https://t.co/0w68CrwL8k Even on a @NVIDIAGeForce 1060 we can convert nearly half a TB of data in 30 mins. 🔥🔥🔥 10x cost saving ftw!
— Joshua Patterson (@datametrician) August 17, 2020
Want an idiomatically Julia version of fastai2? Then join the FastAI.jl project!https://t.co/ZFp3gPB28G
— Jeremy Howard (@jeremyphoward) August 17, 2020
Slides from my #rstatsnyc talk on the widyr package, for widening, operating, and then re-tidying a dataset
— David Robinson (@drob) August 15, 2020
Slides: https://t.co/Zz0b6pa0c3
Package 📦: https://t.co/1gjFrq6qQu pic.twitter.com/PBqXxUzBoY
