DeText: A deep NLP framework for intelligent text understanding https://t.co/HmI5f6RfD3 #Python #NLP #MachineLearning pic.twitter.com/iEtqIi1PPJ
— Python Weekly (@PythonWeekly) August 3, 2020
DeText: A deep NLP framework for intelligent text understanding https://t.co/HmI5f6RfD3 #Python #NLP #MachineLearning pic.twitter.com/iEtqIi1PPJ
— Python Weekly (@PythonWeekly) August 3, 2020
A Keras implementation of “A Simple Framework for Contrastive Learning of Visual Representations” (SimCLR)https://t.co/RUsFe4CQNLhttps://t.co/d87F44gLpn pic.twitter.com/AjfBl8cwxF
— hardmaru (@hardmaru) July 28, 2020
RNNoise is an audio noise suppression package by J-M Valin / https://t.co/iU5eDhK0cX / Mozilla. I love seeing neat practical applications of deep learning, especially when they're open-source :)https://t.co/NgCsJZVWWi
— François Chollet (@fchollet) July 18, 2020
I'm really excited about this project. I think adapters are a useful framework to efficiently leverage task, domain, and language-specific information—and AdapterHub makes it easy to download, train, and share them. https://t.co/06yaXd7g8P
— Sebastian Ruder (@seb_ruder) July 16, 2020
Deep Chernoff Faces: uses a @TensorFlow 2.x implementation of StyleGAN2 to generate the faces that you see on the right.
— 👩💻 DynamicWebPaige @ 127.0.0.1 🏠 (@DynamicWebPaige) July 3, 2020
💻 Blog post: https://t.co/NthkPRxKqz
📒 @GoogleColab notebooks and code: https://t.co/qD9FGCkxxf pic.twitter.com/Es6cS5l8XV
DistilBART is awesome and super fast! Thank you @huggingface for releasing this!
— plotly (@plotlygraphs) June 29, 2020
We built this demo app with Dash in <200 lines that summarizes articles in real time (even on entry-level GPUs).
Code here: https://t.co/N7G2bxflue pic.twitter.com/VpZWlzxzMu
Face Depixelizer
— Bomze (@tg_bomze) June 19, 2020
Given a low-resolution input image, model generates high-resolution images that are perceptually realistic and downscale correctly.
😺GitHub: https://t.co/0WBxkyWkiK
📙Colab: https://t.co/q9SIm4ha5p
P.S. Colab is based on thehttps://t.co/fvEvXKvWk2 pic.twitter.com/lplP75yLha
✨🚗 A @TensorFlow 2.1 and tf.keras implementation of "Super SloMo: High-Quality Estimation of Frames for Video Interpolation (CVPR 2018)".https://t.co/CGTfKeOmEi
— 👩💻 DynamicWebPaige @ 127.0.0.1 🏠 (@DynamicWebPaige) June 19, 2020
The GIF on their README is giving me flashbacks to video-watching attempts during the age of dial-up... 😅 pic.twitter.com/6vmsLIQZMd
Are we done with ImageNet?
— roadrunner01 (@ak92501) June 15, 2020
pdf: https://t.co/WkwBvLSW77
abs: https://t.co/cryNKs6PjT
github: https://t.co/jRKV9aEMRj pic.twitter.com/Aahfuqy0P8
Big GANs Are Watching You: Towards Unsupervised Object Segmentation with Off-the-Shelf Generative Models
— roadrunner01 (@ak92501) June 11, 2020
pdf: https://t.co/0buscthKLU
abs: https://t.co/coBhnX0xZA
github: https://t.co/hcxZFcqXCp pic.twitter.com/i0ii4p6Nl7
Normalizing flows in PyTorch https://t.co/aX9Uwa4k2n #deeplearning #machinelearning #ml #ai #neuralnetworks #datascience #pytorch
— PyTorch Best Practices (@PyTorchPractice) June 9, 2020
Presenting PEGASUS, an approach to pre-training, that uses gap-sentence generation to improve the performance of fine-tuning for #NaturalLanguageUnderstanding tasks, like abstractive summarization. Read more and try the code for yourself ↓ https://t.co/bVFCKGXZMI
— Google AI (@GoogleAI) June 9, 2020