TGINSIGHT SIMILAR POSTS
Chaîne source @OnePlusGuide · Post #2744 · 23 août
🔻SERIE ONEPLUS NORD: 2 NUOVI MODELLI IN ARRIVO?🔻 #ONEPLUS Vi ricordate dei rumor su Billie, il potenziale fratellino low-cost del OnePlus Nord? (Se non sapete di cosa sto parlando, tappatequi) Negli ultimi giorni girano voci (appoggiate dal noto leaker Max J) che sui siti di benchmark siano apparsi Billie 1 e Billie 2, quindi non uno ma ben due smartphone low-cost firmati OnePlus. Riassunto in poche righe, ecco quello di cui si è parlato finora: Vendita ristretta solo agli USA, retro in plastica, Snapdragon 690 5G, carica che arriva solo alla 18W. Vi potrebbero interessare? Fatecelo sapere nei nostri gruppi! Pit — Il nostro canale 👉🏻@oneplusguide I nostri gruppi 👉🏻@oneplusitcommunity
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Recherche : #ml
@repo_science · Post #3688 · 03/11/2023 12:00
#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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@repo_science · Post #3447 · 17/07/2023 15:14
#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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@amneumarkt · Post #687 · 18/07/2025 06:24
#ml https://aryagxr.com/blogs/intro-to-nmc
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@amneumarkt · Post #682 · 27/06/2025 05:30
#ml Machine Learning Visualized — Machine Learning Visualized https://ml-visualized.com/?utm_source=substack&utm_medium=email
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@amneumarkt · Post #617 · 25/08/2024 14:03
#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 · 30/07/2024 06:20
#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 20:53
#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 · 06/07/2024 22:02
#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 #575 · 09/05/2024 19:51
#ml https://github.com/google-research/timesfm
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@amneumarkt · Post #538 · 16/02/2024 11:21
#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 · 09/02/2024 05:35
#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 · 05/02/2024 10:57
#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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