We computer vision researchers rarely look at the individual data points inside our datasets.
Mainly because we are too lazy and/or do not have the right tools.
This needs to change. And now we have a great tool from @TensorFlow datasets team: Know Your Data. A thread.🧵(1/5)
I'd like to share my course on generative models that I taught in the fall. The course covers AR, VAE, GAN, Flow, and EBM, as well as relevant NN stuff: resnets, transformers, etc. I hope some people find this helpful!
https://t.co/OTSr70r5OC
New year, and new challenges! I've decided to do a series of blog posts on deep generative modeling. The first post is out: https://t.co/Dqxg4S2EJP
I hope you'll enjoy it! The next one in ~2 weeks 🤓
Happy to (finally) share SciHive - arXiv on steroids 🚀
✓ Rank trending papers by Twitter
✓ Comment and ask questions on papers
✓ Collaborate within a group
✓ Save private notes
✓ View table of contents
✓ Preview references
✓ Open source
https://t.co/9Kz7YEyC8L
"Man is the most insane species. He worships an invisible God and destroys a visible Nature. Unaware that this Nature he's destroying is this God he's worshipping."
-- Hubert Reeves
Last night I had a dream: I was training a neural net. It would print:
Accuracy: .65
Accuracy: .67
I expected better performance, so I kept tweaking settings. Suddenly,
Accuracy: .91
That's more like it! Hoping for even better, I make a few more tweaks, and --
Accuracy: 1.35
This is an absolutely amazing resource for learning Machine Learning concepts. Python notebooks on the web. You can even download the PDF version of the chapters.
https://t.co/9mVdacvrlr
Bengaluru’s 75-year-old Selvamma goes high-tech using a solar-powered fan to grill corn on the roadside near Vidhana Soudha. The equipment can run LED light and power regulated fan.