TGINSIGHT SIMILAR POSTS
Source channel @olddriverGDstudy · Post #38 · Mar 17
#知识 性爱技巧 有男生问我：爱爱时很快就射，怎么办？我回答：节奏放慢，不要着急插入，而要做足“三个半小时”： 1️⃣狂吻半小时，吻得她透不过气，吻得她嘴肿，让她深切感受到你对她的真实激情； 2️⃣玩弄半小时，在嘴上继续狂吻，在胯下开始抠摸，抠摸她的阴蒂，抠摸她阴道内的各个兴奋点，抠得她忍不住喘气呻吟，全身扭动而顾不上让你再吻； 3️⃣舔阴半小时，上边放开她的嘴，下边抽出你的手，趴下身去，把你的脸紧贴她的阴部，狂吻她的阴唇，狂舔她的阴蒂，狂吸并且狂咽她的阴液，让她浑身发抖，在高潮中连连叫床……这时，这时，你才可以在她“进来，进来，快进来”的连声央求下，从容不迫地挺身而出，掰开她的双腿，奋力插将进去，并且一插到底！这样，即使你很快就射，她也已经像死猪一样顾不上说你什么了！
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Search: #ml
@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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@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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@amneumarkt · Post #687 · 07/18/2025, 06:24 AM
#ml https://aryagxr.com/blogs/intro-to-nmc
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@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 #575 · 05/09/2024, 07:51 PM
#ml https://github.com/google-research/timesfm
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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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