.@data_stephanie showed us how to make amazing race plots with gganimate 📊🤯
— David Robinson (@drob) November 8, 2019
Slides and code here! https://t.co/DFP2LGKxmp#rstatsdc pic.twitter.com/02QvvVlnR8
.@data_stephanie showed us how to make amazing race plots with gganimate 📊🤯
— David Robinson (@drob) November 8, 2019
Slides and code here! https://t.co/DFP2LGKxmp#rstatsdc pic.twitter.com/02QvvVlnR8
New tutorial!🚀 Traffic Sign Classification with #Keras and #TensorFlow 2.0 🛑🚦⚠️
— Adrian Rosebrock (@PyImageSearch) November 4, 2019
- 95% accurate
- Includes pre-trained model
- Full tutorial w/ #Python codehttps://t.co/MkWiTaYKwU 👍#DeepLearning #MachineLearning #ArtificialIntelligence #DataScience #AI pic.twitter.com/20jYvQw7Dw
See a new example combining Dask and PyTorch for scalable batch prediction.https://t.co/9aB6cU2f5A
— Dask (@dask_dev) October 31, 2019
New tutorial!🚀 3 ways to create a #Keras model with #TensorFlow 2.0:
— Adrian Rosebrock (@PyImageSearch) October 28, 2019
1. Sequential
2. Functional
3. Model-subclassing
But when is the right time to use each?
This tutorial answers that question (includes #Python code): https://t.co/mDXqGCWgxs 👍#DeepLearning #AI #DataScience pic.twitter.com/EYUTRzDUg8
"Writing a PyTorch custom layer in CUDA for Transformer" -- nice tips with regard to write custom layers + profiling PyTorch code https://t.co/kxjkvRzt9C https://t.co/Ewf5in22bG
— Sebastian Raschka (@rasbt) October 25, 2019
Samesies for her "R for Psychological Science"https://t.co/R9dFzH0bIB #rstats
— Mara Averick (@dataandme) October 24, 2019
/* summary: @djnavarro is an absurdly excellent writer */ pic.twitter.com/9Ha2jkHk3v
In this #tidytuesday screencast, I analyze a dataset of horror movie ratings, and use lasso regression to predict ratings based on genre, cast, and plot.
— David Robinson (@drob) October 22, 2019
What's 😱👍: Indian, animated, and drama films
What's 🙄👎: Sharks and Eric Robertshttps://t.co/3qj7NoA4Pf #rstats 🧛♂️👻 pic.twitter.com/OBI6x1O2zX
Want to learn how to run Asynchronous Federated Learning in @PyTorch over #websockets?
— OpenMined (@openminedorg) October 22, 2019
This blogpost tutorial by #SilviaGandy shows how you can use #PySyft's WebSocketWorkers to do just that!#100DaysOfMLCode #privacyhttps://t.co/d1roRjpdDr pic.twitter.com/KW9mltEGYC
Non-Gaussian forecasting using the new fable package: https://t.co/18A3jL8rFV #rstats pic.twitter.com/VzGjNmzkhY
— Rob J Hyndman (@robjhyndman) October 17, 2019
🦇 Cuz it's helpful, *and* I had bat emojis kicking around…
— Mara Averick (@dataandme) October 12, 2019
🗂 "Apply functions to grouped data and write each element to disk" by @LuisDVerdehttps://t.co/B8ZnOrwI3B #rstats #purrr pic.twitter.com/AuYrD59USh
🏀 @flowingdata combines R, hoops, annotation, and stellar GIFcraft…
— Mara Averick (@dataandme) October 11, 2019
🎞 "How to Make Animated Visualization GIFs w/ ImageMagick" https://t.co/RvbhBeoajs #dataviz pic.twitter.com/E9bqPH0Zyb
As promised, the first tutorial showing how to use the fastai.medical.imaging library is now available.
— Jeremy Howard (@jeremyphoward) October 9, 2019
It covers analyzing DICOM metadata with a Pandas extension method; combining metadata, pixel stats, & labels; working with data types; viewing; & morehttps://t.co/CqsLkojMSx pic.twitter.com/Zzot76l3uY