⚡️ Making its CRAN debut…
— Mara Averick (@dataandme) October 22, 2019
📦 "readthat: Read Text Data" by @kearneymw https://t.co/V5HMXW32km #rstats pic.twitter.com/peXrrtotbm
⚡️ Making its CRAN debut…
— Mara Averick (@dataandme) October 22, 2019
📦 "readthat: Read Text Data" by @kearneymw https://t.co/V5HMXW32km #rstats pic.twitter.com/peXrrtotbm
Want to learn how to run Asynchronous Federated Learning in @PyTorch over #websockets?
— OpenMined (@openminedorg) October 22, 2019
This blogpost tutorial by #SilviaGandy shows how you can use #PySyft's WebSocketWorkers to do just that!#100DaysOfMLCode #privacyhttps://t.co/d1roRjpdDr pic.twitter.com/KW9mltEGYC
tidybayes killing it in the visualizing uncertainty department https://t.co/jMRy7buv6J pic.twitter.com/WiZ1doKKw4
— tj nightmahr 🎃🍕 (@tjmahr) October 21, 2019
Microsoft open sourced their visual data exploration tool SandDance https://t.co/L40EDpSvoZ pic.twitter.com/PCRdZvcmeR
— Nathan Yau (@flowingdata) October 18, 2019
💥 @LysandreJik just published a great comparison of inference speed & memory requirements for a wide range of recent NLP models:
— Thomas Wolf (@Thom_Wolf) October 18, 2019
- RoBERTa, Bert, GPT2, XLNet, DistilBert, CTRL...
- comparing PyTorch & TensorFlow 2.0
- on typical CPU and GPU setups
- summarizing good-practices👇 https://t.co/2G3cYaUozL
TensorFlow 1.15.0 has been released! We do not expect to update the 1.x branch with features, although we will issue patch releases to fix vulnerabilities for at least one year.
— TensorFlow (@TensorFlow) October 17, 2019
See the full release notes for more details on added features and changes ↓https://t.co/UQTEYtADSO
Mypy 0.740 is out, with type checking of str.format calls and improved checking of unannotated functions. https://t.co/XMzAuE5bBv
— The Mypy Project (@mypyproject) October 17, 2019
Captum – model interpret-ability & understanding library for PyTorch
— ML Review (@ml_review) October 17, 2019
Includes a web interface for easy visualization and access to a number of interpretability algorithms: Integrated Gradients, Saliency Maps, Smoothgrad, Vargrad and othershttps://t.co/QHPlf29n1v pic.twitter.com/bSmDpuZV2u
Non-Gaussian forecasting using the new fable package: https://t.co/18A3jL8rFV #rstats pic.twitter.com/VzGjNmzkhY
— Rob J Hyndman (@robjhyndman) October 17, 2019
We're extremely excited to release our BoTorch paper!
— Andrew Gordon Wilson (@andrewgwils) October 16, 2019
Scalable, flexible, and modular Bayesian optimization integrated with GPyTorch and @PyTorch. It's been a pleasure working with @eytan, Max, and team.
paper: https://t.co/NUe6ve4i8p
code: https://t.co/RyEp1NneS4 pic.twitter.com/jc18vkEQ12
VS Code Adds Native Editing of Jupyter Notebooks https://t.co/L6vsu3s3EW
— PyCoder’s Weekly (@pycoders) October 16, 2019
"ExBert - A Visual Analysis Tool to Explore Learned Representations in Transformers Models" -- this looks like a nice one! Tool: https://t.co/YZqHvUBD5h and paper: https://t.co/NEJG4LKGzP pic.twitter.com/q96JWrWfD2
— Sebastian Raschka (@rasbt) October 15, 2019