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Source channel @githubtrending · Post #15120 · Sep 5

#shell#cloudflare#grpc_cloudflare#httpupgrade#hysteria2#nginx#reality#reality_grpc#shell#sing_box#trojan#trojan_grpc#tuic_v5#v2ray#vless#vmess#websockettlscdn_cloudflare_ip#xray#xray_core#xray_install#xtls_rprx_vision v2ray-agent is a tool that helps you quickly install and manage proxy servers using popular cores like Xray-core and sing-box. It supports many protocols such as VLESS, VMess, Trojan, and more, and automatically handles SSL certificates for secure connections. You can easily manage users, ports, and subscriptions through a simple menu. It also offers features like traffic routing, domain blocking, and P2P download control, which can help you unblock streaming services and control internet access. Installation is simple with a one-command script, making it convenient to set up and maintain your proxy server securely and efficiently. https://github.com/mack-a/v2ray-agent

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Repositorio data science

@repo_science · Post #3688 · 11/03/2023, 12:00 PM

#ML 😎 FREE RESOURCES TO LEARN MACHINE LEARNING Intro to ML by MIT Free Course Machine Learning for Everyone FREE BOOK ML Crash Course by Google Advanced Machine Learning with Python Github Practical Machine Learning Tools and Techniques Free Book Python Machine Learning for beginners ----- Main channel: @repo_science Coupons: @freecoupons_reposcience -----

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Repositorio data science

@repo_science · Post #3447 · 07/17/2023, 03:14 PM

#ML 🧠 Machine Learning Expert 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. ✍️Ryan Doan | Ex-Amazon ML Infrastructure Engineer 🌐En 📆2022 🔗Link ----- Main channel:@repo_science Coupons:@freecoupons_reposcience -----

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Am Neumarkt 😱

@amneumarkt · Post #682 · 06/27/2025, 05:30 AM

#ml Machine Learning Visualized — Machine Learning Visualized https://ml-visualized.com/?utm_source=substack&utm_medium=email

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@amneumarkt · Post #617 · 08/25/2024, 02:03 PM

#ml 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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@amneumarkt · Post #607 · 07/30/2024, 06:20 AM

#ml 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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@amneumarkt · Post #596 · 07/07/2024, 08:53 PM

#ml 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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@amneumarkt · Post #595 · 07/06/2024, 10:02 PM

#ml Schmidhuber J. Deep Learning: Our Miraculous Year 1990-1991. In: arXiv.org [Internet]. 12 May 2020 [cited 7 Jul 2024]. Available: https://arxiv.org/abs/2005.05744

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@amneumarkt · Post #538 · 02/16/2024, 11:21 AM

#ml 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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@amneumarkt · Post #532 · 02/09/2024, 05:35 AM

#ml 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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@amneumarkt · Post #531 · 02/05/2024, 10:57 AM

#ml 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.

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