Tune in:
- ML Hero interviews: https://t.co/Nrpqa4p2yj
- News & Short Series: https://t.co/toS556E9OV
- Blog versions: @hackernoon: https://t.co/h1rCIryXwa
Excited to be on this Quadruple Quadruple Kaggle Grandmaster panel π
And no, that's not a typo.
Tune in this Friday at 9:30pm IST: https://t.co/Il8ZzxsmBu
We may reveal a secret or two π
CTDS Show is excited to be a community partner for the @neo4j#NODES2021 tomorrow!π΅
Sign up: https://t.co/RgwTgkvsjt
Join us tomorrow to learn from graph experts and their impact
My interview with THE @Sentdex is today! π΅
Final call for any questions that you'd want me to ask him π
I've spent ~100 hours combing through Harrison's AMAZING journey.
I hope you'll find it as fascinating as I did!
ETA to release ~2 weeks:
https://t.co/oidObI8grh
The @fastdotai community has always been very active on Twitter π
Many people will be starting their journey this week, thanks to @amaarora
If you're trying to find your 'fastai peers', here's a list I have been putting together: https://t.co/ip4mfmkxfv
I'm *really* excited to be interviewing THE @Sentdex next week ππ΅
Please send any questions that you'd want us to discuss on @ctdsshow
Interview will be out by 3rd week of June: https://t.co/oidObI8grh
Meta Learning is out! ππ₯³
Above all, thank you for the warmth and support that you have shown me here on Twitter. That means the world to me and is completely out of this world π₯°
If you would like to continue helping me, any feedback would be greatly appreciated π
It's hard for me to contain my excitement as I share this with you!
@fastdotai has been at the core of all my learnings and I look forward to sharing the love for this library with you through fastbook reading sessions at @wandb for the next ~20 weeks!
A thread:
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Chai Time Data Science is seeking interns π
If sharing stories of ML Heroes & helping ML community is of interest to you, I'm seeking help for:
- π₯ Video Editing
- π± Managing social media
Sign up here if you're interested: https://t.co/8lHTNHRmbV
I'll be moderating the discussion on Putting Models into Production.
If you have any Qs for the panel, please send them my way. π΅π
PS: Major correction π, I'm not a Grandmaster π
Chai Time Data Science has crossed 200,000 Streams overall! π
Thank you so so much, everyone! π΅
Time to work on Season 2 Launch: https://t.co/DtrUj8CzII
What would you like to see? What can I do better?
Visformer: The Vision-friendly Transformer
tl;dr: there are 2 modes of training:
- "base": short training, Crop-Flip augmentation
- "elite": long training, complex (RandAugment-like) augmentation.
Changes in network lead to opposite results in these modes
https://t.co/y8fM2H5r1I
"Could @huggingface Accelerate really be this easy?" I asked myself, and the result is this blog post where we take a deep-dive into the source code of the package.
https://t.co/i3jxSgTHtC
Thanks @GuggerSylvain - you've done it again!!
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π Published new content on H2O AutoML π
β Beginner friendly
β Complete with code
β End-to-end examples
π Available on GitHub
π Available on Colab
π Available on Kaggle
More coming soon!
Stay home if possible. Stay safe! π·
https://t.co/dzVUgAjCjI
Weekened watch @MLStreetTalk interview with @fchollet:
https://t.co/rZ9hYnqyY7
I feel MLST is like a Netflix special of the world of Machine Learning. The quality-of the podcast & production just gets better exponentially with every episode π±
THREAD: An enormous thank you to everyone who shared their insights on community participation! β€οΈ It has been amazing to learn from you π
Article with all the responses coming soon.
I would also like to give additional thanks to @bhutanisanyam1.
Here is why...