pyscript wrapper for D3
— Hamel Husain (@HamelHusain) April 30, 2022
WOW, Data Scientists can write D3 with Python now
This is the coolest thing that's happened to DataViz in a while https://t.co/X6DF0Uk7E2
pyscript wrapper for D3
— Hamel Husain (@HamelHusain) April 30, 2022
WOW, Data Scientists can write D3 with Python now
This is the coolest thing that's happened to DataViz in a while https://t.co/X6DF0Uk7E2
If you are working in Python, and find yourself in a need of encoding categorical variables for various ML tasks, I'd strongly encourage you to take a look at the Category Encoders library. It's a very good and fairly comprehensive sklearn-style library. https://t.co/N8wubPlKDF
— Bojan Tunguz (@tunguz) April 28, 2022
I'm starting to fall in love with NVTabular 🥰
— Radek Osmulski 🇺🇦 (@radekosmulski) April 14, 2022
✅ beautiful functional API
✅ abstracts away hardware so that it can run on anything
✅ utilizes the GPU 🔥
But there is one unintuitive Python feature you need to know about to read NVTabular code with ease.
>>> a thread 🧵 <<< pic.twitter.com/bH5gmvBA0D
Improve your #Python coding workflow with the #JupyterLab inspector ☺️https://t.co/2qX5UuwXn0@timdumol @SylvainCorlay @ccordoba12 @CAM_Gerlach @ProjectJupyter pic.twitter.com/f4glWEK3ak
— Martin Renou (@martinRenou) April 11, 2022
Presenting ALX, an open-source library for distributed matrix factorization that makes efficient use of the #TPU architecture, enabling a high-performance implementation on a large-scale cluster of TPU devices. Learn more and grab the code → https://t.co/e6O6jQ8eVM pic.twitter.com/TekGA7Dqng
— Google AI (@GoogleAI) April 8, 2022
The new Bentley machine learning operation framework combines Microsoft Azure Machine Learning with the power of PyTorch to help you develop and deliver AI models faster and more reliably. Would you like to see how? Read on. https://t.co/IwvfIhkMUi
— PyTorch (@PyTorch) April 7, 2022
These diagnostic plots are 🔥 #rstats https://t.co/v51Pp6ccxD
— JD Long (@CMastication) March 31, 2022
Do you use (or want to use) #Docker and #rstats for model deployment? The vetiver package can help you generate a Dockerfile to deploy your model as an API, and we would love feedback from early users! 💜https://t.co/oxaVXTNFR3 pic.twitter.com/K8vuSn72x4
— Julia Silge (@juliasilge) March 24, 2022
Very interesting work on Unsupervised Feature Selection using Supervised Algorithms. It turns out that even for unsupervised learning, XGBoost is all you need. :)
— Bojan Tunguz (@tunguz) March 12, 2022
Blog post: https://t.co/o2nC7wUl7d
Code repo: https://t.co/aOR3mJ9VEy#machinelearning #unsupervisedlearning pic.twitter.com/PZVKxGBgfl
Announcing PyTorch 1.11, TorchData, and functorch!
— PyTorch (@PyTorch) March 10, 2022
Highlights:
- TorchData, a new library for common modular data loading primitives
- functorch adds composable function transforms
- DDP static graph optimizations in stable
Learn more👇https://t.co/WAIjrEguOg
Introducing Ithaca, the first deep neural network for textual restoration, as well as geographical and chronological attribution of ancient Greek inscriptions.
— DeepMind (@DeepMind) March 9, 2022
Out today in @nature, Ithaca aims to assist historians & better understand ancient history: https://t.co/iGcx323enn 1/ pic.twitter.com/R5XnHfDFAi
This looks really exciting for time series work. The original project from @robjhyndman in R is an absolute classic, and to have it available in Python is huge.
— Jeremy Howard (@jeremyphoward) February 24, 2022
Even better - it's an #nbdev project which means it's got great docs and tests and is easy to contribute to. https://t.co/22o6D7EHFQ