Very useful package for PyTorch: "torchbearer: A model fitting library for PyTorch" https://t.co/kSSGlJw7dM pic.twitter.com/08ms6MvHQt
— Learn PyTorch (@learnpytorch) February 6, 2019
Very useful package for PyTorch: "torchbearer: A model fitting library for PyTorch" https://t.co/kSSGlJw7dM pic.twitter.com/08ms6MvHQt
— Learn PyTorch (@learnpytorch) February 6, 2019
I really love the line-of-code completions in the new https://t.co/TcfoSNq6b4. Thanks for the demo @asmith!
— Guido van Rossum (@gvanrossum) February 5, 2019
TextFSM: Python Module for Parsing Semi-Structured Text https://t.co/6iNCjQGS6r
— PyCoder’s Weekly (@pycoders) February 4, 2019
ArchiveBox - 🗃 The open source self-hosted web archive. Takes browser history/bookmarks/Pocket/Pinboard/etc., saves HTML, JS, PDFs, media, and more... https://t.co/kLJcG6nwaB
— Python Trending (@pythontrending) February 4, 2019
This is a super cool resource: Papers With Code now includes 950+ ML tasks, 500+ evaluation tables (including SOTA results) and 8500+ papers with code. Probably the largest collection of NLP tasks I've seen including 140+ tasks and 100 datasets.https://t.co/lTAGE7LGZY pic.twitter.com/wfSyTplBR3
— Sebastian Ruder (@seb_ruder) February 1, 2019
WOW! Pandoc now supports reading / writing @ProjectJupyter notebooks! It's a new feature so use it and break it and help make it better! https://t.co/CDu73jCER0 pic.twitter.com/qMOqe7VEDl
— Chris Holdgraf (@choldgraf) February 1, 2019
spacy-stanfordnlp - 💥 Use the latest StanfordNLP research models directly in spaCy https://t.co/CsOXdw4qbO
— Python Trending (@pythontrending) February 1, 2019
Take your NLP to the next level with LASER, a newly open-sourced @facebookai
— DataScienceNigeria (@DataScienceNIG) February 1, 2019
natural language processing toolkit, which performs zero-shot cross-lingual transfer with >90 languages- including languages where training data is extremely limited.
GitHub: https://t.co/DAKPZGzgPd pic.twitter.com/10wpiWzAOs
DoWhy – Python library to estimate causal effects by @MSFTResearch
— ML Review (@ml_review) January 31, 2019
Based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks. https://t.co/wEh7EHwms1
Xfer: is an open source framework we’ve released for transfer learning of Neural Networks using GPs and BNNs with MXNet.
— Neil Lawrence (@lawrennd) January 31, 2019
Here’s a blog post on the work from @adamianou https://t.co/AYO0Zq9ZdV
Did you know that fastai can provide all the information necessary for you to get help, with a single command? It even includes the markdown to make it format properly in github issues or https://t.co/ylvw7vGYzT!
— Jeremy Howard (@jeremyphoward) January 29, 2019
Yup, everything is fast in fastai - even getting help! :D pic.twitter.com/J5cyUzzaan
LASER - A library to calculate and use multilingual sentence embeddings. https://t.co/SRICGx8Vf3 #python
— Python Weekly (@PythonWeekly) January 28, 2019