Jean Metz
1.3K posts

Jean Metz
@JMetzz
PhD | Machine learning engineer | coffee lover | cyclist
Nuremberg, Bavaria 가입일 Aralık 2008
433 팔로잉202 팔로워

Remote Pair Programming Good Practices: A Thread.
Found the slides of a presentation that @qcoding and I gave to the entire CTO Org at Amex two years ago when we were both there.
Thought it had a lot of great stuff that could still be useful to others.
Why not share?
🧵




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@jarchitects @axelsegers If you zoom enough you will see that I'm featured in those three pictures on the white board 😊. What a good time we had. Success on 2023!!!
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Jean Metz 리트윗함

Important announcement!
Today we launch a new Twitter-like space for the AI community - Sigmoid Social.
We hope to ensure the thriving AI Twitter community can live on by maintaining this Mastodon instance going forward.
Join here:
sigmoid.social
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Ever struggled using @PyTorch to train deep learning on Geospatial data? Say no more. We developed a system (GeoTorch) that makes spatiotemporal deep learning in PyTorch a cakewalk👇🏽
kanchanchy.github.io/geotorch/
#geospatial #DeepLearning #ArtificialIntelligence #DataScience

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FSNet - Learning time-series fast and slow; quickly adapt to simultaneously deal with abrupt changing and repeating patterns in time series.
Paper:
arxiv.org/abs/2202.11672
Python GitHub:
github.com/salesforce/fsn…

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🎁 Such an absolute gift of a paper, describing definitions for key terms and design considerations for natural language prompts. And beautiful visualizations!
Recommendations to consider: pre-trained model choices; prompt+answer engineering; and more.
📄arxiv.org/abs/2107.13586

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Want to have a super strong Career in Tech?
Build enough career capital to become over the years this rare kind of Software Engineer @GergelyOrosz described perfectly on his newsletter this week.
Not a Jack of All Trades Master of None. A Jack of Many Trades, Master of Some.🧵


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Jean Metz 리트윗함

CS109A Data Science course materials @Harvard are free and open for everyone!
1. Lecture notes
2. R code, Python notebooks
3. Lab material
4. Advanced sections
Learn here: harvard-iacs.github.io/2019-CS109A/pa…

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