Buried at the end of this post is a neat discussion of using SWA-Gaussian to get uncertainty estimates from deep learning models. I’m looking forward to checking that out. https://t.co/XU0arMvjGt
— Sean J. Taylor (@seanjtaylor) April 29, 2019
Buried at the end of this post is a neat discussion of using SWA-Gaussian to get uncertainty estimates from deep learning models. I’m looking forward to checking that out. https://t.co/XU0arMvjGt
— Sean J. Taylor (@seanjtaylor) April 29, 2019
One line change: pic.twitter.com/2DWLuQcjue
— Delip Rao (@deliprao) April 29, 2019
Explacy by @tylerneylon gives you a very nicely formatted dependency tree and a table including part-of-speech tags and lemmas.https://t.co/hJnqKEHqO3 pic.twitter.com/ALW7WdgvZC
— Ines Montani 〰️ (@_inesmontani) April 29, 2019
Stochastic Weight Averaging: a simple procedure that improves generalization over SGD at no additional cost.
— PyTorch (@PyTorch) April 29, 2019
Can be used as a drop-in replacement for any other optimizer in PyTorch.
Read more: https://t.co/IRhz40AZKU
guest blogpost by @Pavel_Izmailov and @andrewgwils pic.twitter.com/yU0HKDYr7v
https://t.co/qHvO6kotwe - An inline Bash script runner, for Python. https://t.co/Y9G4pphxed #python #bash
— Python Weekly (@PythonWeekly) April 29, 2019
Just released Altair version 3.0! This is a huge update, with many new visualization features and bug-fixes thanks to the hard work of the @vega_vis team.
— Jake VanderPlas (@jakevdp) April 26, 2019
Check it out: https://t.co/PCyrIOTcvv pic.twitter.com/0YT2ckQizl
🕵️♂️ Some nice funs for quick EDA…
— Mara Averick (@dataandme) April 25, 2019
🔍 "inspectdf: Tools for Exploring and Comparing Data Frames" by @rushworth_a https://t.co/xcllMCpqPu #rstats pic.twitter.com/IGvzTSHhRN
Pytorch implementation of Octave convolution https://t.co/6Hygcy8A0W #pytorch #deeplearning #neuralnetwork
— PyTorch Best Practices (@PyTorchPractice) April 24, 2019
New Tesla T4 available in google collaboratory. This is one of the best GPUs you can buy, includes fast half-precision tensor cores - and you can use it for free! :Ohttps://t.co/8QvR2a1dIp pic.twitter.com/YqIvI9jUal
— Jeremy Howard (@jeremyphoward) April 23, 2019
ICYMI, 🕸 Fresh off a new CRAN release…
— Mara Averick (@dataandme) April 23, 2019
"{graphlayouts}: New layout algorithms for network viz in R" 👨💻 @schochastics https://t.co/UwW2XFGpz9 #rstats #dataviz #networkviz pic.twitter.com/WqrVYDl1zP
Did you know that there's now a #Python version of the infamous #rstats data.table package? 📦 R data.table creator, @MattDowle, teamed with @h2oai colleague @pstetsenko to create Py @datatable. @sudalairajkumar has a @kaggle notebook to get you started: https://t.co/fXbCCR85af pic.twitter.com/dvmpQlsp1S
— Erin LeDell (@ledell) April 23, 2019
Exciting new work by Park, Chan, et al. to improve ASR models with data augmentation.
— Jeff Dean (@JeffDean) April 22, 2019
"Instead of augmenting the input audio waveform as is traditionally done, SpecAugment applies an augmentation policy directly to the audio spectrogram." https://t.co/Pluccv89RR