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Strapi is a free, open-source headless content management system that lets you manage content easily and flexibly, whether you host it yourself or use Strapi Cloud. It works with many databases and lets you build custom APIs, routes, and plugins to fit your needs. You can use any frontend technology you like, such as React, Vue, or Angular, and it comes with a modern, customizable admin panel. Strapi is fast, secure, and scalable, making it simple to deliver content across websites, apps, or devices. This means you get full control over your content and how it’s displayed, saving time and effort while keeping your project future-proof[1][2][3].
https://github.com/strapi/strapi
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El aprendizaje automático es un vasto campo con muchos conceptos clave que conocer. Nuestro curso intensivo cubre todos los componentes básicos que necesita para sumergirse en el aprendizaje automático del mundo real.
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What’s Really Going On in Machine Learning? Some Minimal Models—Stephen Wolfram Writings
https://writings.stephenwolfram.com/2024/08/whats-really-going-on-in-machine-learning-some-minimal-models/
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Meta's second version of segment anything.
https://github.com/facebookresearch/segment-anything-2
They have a nice demo:
https://sam2.metademolab.com/
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I was searching for a tool to visualize computational graphs and ran into this preprint. The hierarchical visualization idea is quite nice.
https://arxiv.org/abs/2212.10774
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Like a dictionary
Kunc, Vladim’ir, and Jivr’i Kl’ema. 2024. “Three Decades of Activations: A Comprehensive Survey of 400 Activation Functions for Neural Networks.” arXiv [Cs.LG], February. http://arxiv.org/abs/2402.09092.
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I got interested in satellite data last year and played with it a bit. It's fantastic. The spatiotemporal nature of it brings up a lot of interesting questions.
Then I saw this paper today:
Rolf, Esther, Konstantin Klemmer, Caleb Robinson, and Hannah Kerner. 2024. “Mission Critical -- Satellite Data Is a Distinct Modality in Machine Learning.” arXiv [Cs.LG], February. http://arxiv.org/abs/2402.01444.
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Jelassi S, Brandfonbrener D, Kakade SM, Malach E. Repeat after me: Transformers are better than state space models at copying. arXiv [cs.LG]. 2024. Available: http://arxiv.org/abs/2402.01032
Not surprising at all when you have direct access to a long context. But hey, look at this title.