Tag: tutorial

🙌 There's something about ogling other house-style guides for viz…
📊 "Urban Institute Data Visualization style guide" https://t.co/W2kcMgIDoR via @urbaninstitute #dataviz pic.twitter.com/o1kBNPqQfG

— Mara Averick (@dataandme) June 7, 2019

Still one of the 🐐 troves of viz knowledge around!
A veritable #dataviz education:
"Visualization Analysis & Design" w/ all @tamaramunzner's talks 🎉! https://t.co/CxTLoO9u8W #infovis pic.twitter.com/2sW14IsgkY

— Mara Averick (@dataandme) June 6, 2019

Messy Data? Try this video on "Cleaning and Tidying Data" using Pandas from our PyData DC Meetuphttps://t.co/MhSDsRAwPN

— PyData (@PyData) June 5, 2019

There's a bunch of FUD around Python 3.7's dataclasses, and how they relate to the the attrs library. My colleague @fcurella does a wonderful job cutting through the noise, explaining how they relate, and laying out why you might choose one or the other: https://t.co/aLSs3NAxU4

— jacobian (@jacobian) June 4, 2019

Here's regression example on the Ames Housing Price dataset. This dataset turns out to be great for demonstrating how to vectorize structured data, and how to handle missing features. https://t.co/aEQDn38psw

Thanks to @micahjsmith for suggesting this dataset!

— François Chollet (@fchollet) June 3, 2019

Colab for our tutorial #NAACLTransfer @seb_ruderhttps://t.co/mmnQCS3UHV

— Thomas Wolf (@Thom_Wolf) June 2, 2019

Here are the materials for our @NAACLHLT tutorial on Transfer Learning in NLP with @Thom_Wolf @swabhz @mattthemathman:
Slides: https://t.co/54KVG0K85z
Colab: https://t.co/iqWPtVFSVg
Code: https://t.co/bka5EsuYtP#NAACLTransfer pic.twitter.com/6wPZu9bmc7

— Sebastian Ruder (@seb_ruder) June 2, 2019

Last reminder! Slides and notebooks for my #naacl2019 tutorial on Modeling Language Change are online. Follow all the action from the comfort of your own laptop.https://t.co/8cW8d342Ar

— Jacob Eisenstein (@jacobeisenstein) June 2, 2019

Exploring Python Using GDB https://t.co/UH4bqSjbU7

— PyCoder’s Weekly (@pycoders) May 31, 2019

To help data scientists accelerate their applications, @RAPIDSAI has just published new notebooks that add user-centric restructuring and easy docker integration.

— NVIDIA AI Developer (@NVIDIAAIDev) May 30, 2019

An self-contained image segmentation example (model trained from scratch on the Oxford Pets dataset): https://t.co/GLbowTf9ie

— François Chollet (@fchollet) May 29, 2019

The Illustrated BERT, ELMo, and co. (How NLP Cracked Transfer Learning) https://t.co/ENjHsIQ1HY

— Nando de Freitas (@NandoDF) May 29, 2019