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
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
Build and Deploy Machine Learning Apps with @Gradio by Manuel Gil
— AK (@ak92501) March 25, 2022
medium: https://t.co/7k6QcnbmNj pic.twitter.com/I9DUIXMsIx
Since it's a super helpful library for computing metrics in deep learning, and since there are a few common questions about it, I just wrote a short post on
— Sebastian Raschka (@rasbt) March 24, 2022
"TorchMetrics -- How do we use it, and what's the difference between .update() and .forward()?" https://t.co/RtxIPRvHTv
How to store, use, and re-use @RStudio code snippets: https://t.co/40bSHxaSPE by @sharon000
— Kirk Borne (@KirkDBorne) March 1, 2022
—————#BigData #MachineLearning #AI #DataScientists #DataScience #Coding #Rstats #RStudio
———
Source for graphic: https://t.co/CBlOW6YJmG pic.twitter.com/9kweyrW31V
Curious about recommender models?
— Radek Osmulski 🇺🇦 (@radekosmulski) February 24, 2022
Interested in endowing models from other domains with some of their superpowers?
Please join me on a whirlwind tour of 6 recsys architectures!
>> a thread 🧵 << pic.twitter.com/xaPtPKqTUF
🐍 Am loving this tutorial from @jeremyphoward, which shows a Python-based way to create and orchestrate @github Actions:https://t.co/ZdsRdMk6GS pic.twitter.com/H8L5xe3N1z
— 👩💻 Paige Bailey #BlackLivesMatter (@DynamicWebPaige) February 13, 2022
The Annotated S4 (https://t.co/Qyylpwo6J6 /w @siddkaramcheti)
— Sasha Rush (@srush_nlp) January 12, 2022
A step-by-step guide for building your own 16,000-gram language model... pic.twitter.com/tcVac4pSgd
If you'd like to learn the @JuliaLanguage and you know Python, then this tutorial Colab notebook is for you. I just updated it to the latest Julia 1.7.1 version:https://t.co/0ljztliJNv
— Aurélien Geron (@aureliengeron) January 9, 2022
Enjoy! 🙂
Just came across this eminently readable and beginner friendly introduction to Transformers. Probably the best such text I've seen.
— Bojan Tunguz (@tunguz) December 7, 2021
"Transformers from Scratch"https://t.co/qwI75Ezu9O#AI #ML #DS #NLP #artificialintelligence #machinelearning #datascience 1/2 pic.twitter.com/vvhFuzRdC9
🎉Part 2- Summary of 10 summaries on:
— AI Fast Track (60/60) (@ai_fast_track) December 6, 2021
Tips & Trick & Best Practices in training (not only) object detection models.
Don't miss any of those posts, follow @ai_fast_track to catch them in your feed.
🎁 Summary of summaries: ... pic.twitter.com/VLcWNkMaph
Now free (formerly $99): Ari Lamstein's 2 online courses on using his {choroplethr} #rstats package to make maps with R.
— Sharon Machlis (@sharon000) December 2, 2021
Mapmaking in R with Choroplethr https://t.co/XDyzEQHvta
Shapefiles for R Programmers https://t.co/4tGzVvhjz4#rspatial #gis #dataviz pic.twitter.com/xWpfvERz0X
Differential Inference: A Criminally Underused Tool (https://t.co/zSwhvk806r)
— Sasha Rush (@srush_nlp) November 30, 2021
An annotated talk about elementary probability (coins&dice) in pytorch. Nothing new, just think we should mostly do discrete inference with auto-diff.
Slides: https://t.co/tJHQlLwNrp pic.twitter.com/rq37IuEuh6