Release of MadMiner v0.1.0
— Kyle Cranmer (@KyleCranmer) November 16, 2018
A software package to "mine gold" from of MadGraph + @PyTorch implementations of our recent likelihood-free inference techniques.
Also supports Delphes for fast detector simulation #ImplicitModels.
(nice work Johann & Felix!)@iris_hep @diana_hep pic.twitter.com/VCap34ckiY
chartify - Python library that makes it easy for data scientists to create charts. https://t.co/YKPWutlnlB
— Python Trending (@pythontrending) November 15, 2018
Announcing NVIDIA Transfer Learning Toolkit-- a new toolkit that offers highly optimized pre-trained models and powerful features such as pruning for developers creating and deploying IVA solutions using #deeplearning. - https://t.co/XxEMc2gENq pic.twitter.com/39U7EC00qY
— NVIDIA AI Developer (@NVIDIAAIDev) November 14, 2018
Our new data blocks API is the first ml API with such extensive label engineering support that I'm aware of 😊https://t.co/gOrTeD99TW https://t.co/1QUGrP2vSk
— Jeremy Howard (@jeremyphoward) November 13, 2018
one of my "claims to fame" in #rstats 😁🙄😬 is the reprex package, which makes this less agonizing
— Jenny Bryan (@JennyBryan) November 10, 2018
it's a little thing and yet I think code-rich communication is pretty importanthttps://t.co/PW5Kj6Fw2W
and it's been ported to #python !https://t.co/3cI78UtLvp
There's a machine learning library called “Shogun” (将軍) that has been around since 1999. It supports 8+ different languages. See one of the examples on Gaussian processes: https://t.co/do51LiKoeB
— hardmaru (@hardmaru) November 6, 2018
Also just added a function for computing the performance of any supervised model (classifier or regressor; assuming it has a fit+predict function) via the (pessimistic) out-of-bag bootstrap, the (optimistic) .632 Bootrap, and the .632+ Bootstrap: https://t.co/s62yswQkJV
— Sebastian Raschka (@rasbt) November 5, 2018
XGBoost v0.81 is here https://t.co/MQouTx8JxK checkout the new features(larger scale distributed experience), learning to rank, gpu support
— XGBoost (@XGBoostProject) November 5, 2018
Xarray is an open source library providing high-level, easy-to-use data structures and analysis tools for working with multidimensional labeled datasets and arrays in #Python.https://t.co/VoJK9lgb5j#NumFOCUS Sponsored Project since 2018#xarray @xarray_dev pic.twitter.com/CuxXMbp1dK
— PyData (@PyData) November 4, 2018
A raytracer written in PyTorch https://t.co/XJeGtxiqlm #deeplearning #machinelearning #ml #ai #neuralnetworks #datascience #pytorch
— PyTorch Best Practices (@PyTorchPractice) November 3, 2018
Fast and flexible AutoML with learning guarantees. https://t.co/f3c67OT7iw #deeplearning #machinelearning #ml #ai #neuralnetworks #datascience #tensorflow
— TensorFlow Best Practices (@TFBestPractices) November 3, 2018
Rediscovering this 📦 (for 🏀, obvi)
— Mara Averick (@dataandme) November 3, 2018
🔍 "anomalize: Tidy Anomaly Detection" by @mdancho84 & @dvaughan32 https://t.co/NLo6oPUofr via @bizScienc #rstats pic.twitter.com/fBB5t8HxyT
