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Admin: @Raminmousa ID: @Machine_learn link: https://t.me/Machine_learn
Machine Learning for High-Risk Applications
@Machine_learn
با عرض سلام در يكي از پروژه هاي طبقه بندي سرطان پوست نياز به مشاركت داريم. جايگاه نفر سوم خالي مي باشد.
🔸🔻🔸🔻🔸🔻🔻
@Raminmousa
📃Can social network analysis contribute to supply chain
management? A systematic literature review and
bibliometric analysis
📎 Study paper
@Machine_learn
OpenAI o3-mini System Card
📚 Reed
@Machine_learn
🐋 DeepClaude git clone https://github.com/getasterisk/deepclaude.git
cd deepclaude
▪ Github
▪Docs
@Machine_learn
Natural Language Processing with Transformers Building Language Applications
with Hugging Face
#Book
@Machine_learn
⭐️ Fast Think-on-Graph: Wider, Deeper and Faster Reasoning of Large Language Model on Knowledge Graph
🖥 Github: https://github.com/dosonleung/fasttog
📕 Paper: https://arxiv.org/abs/2501.14300v1
@Machine_learn
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Paper submitted by #DeepSeek team has generated significant attention in the AI community.
This work addresses the enhancement of reasoning capabilities in Large Language Models (LLMs) through the application of reinforcement learning techniques. The authors introduce a novel framework, DeepSeek-R1, which aims to improve LLM reasoning abilities by incorporating incentives for logical reasoning processes within their training. This integration of reinforcement learning allows LLMs to go beyond basic linguistic processing, developing sophisticated reasoning methods that can boost performance across a wide array of complex applications.
This approach has cause lots of discussions in different communities, but it definitely opens up the whole new direction of development for the research.
Paper: https://arxiv.org/abs/2501.12948
#nn #LLM
@Machine_learn
📃 Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development
📎 Study the paper
@Machine_learn
🎬 Random Graphs
🎞 Watch
▫️Part 1
▫️Part 2
@Machine_learn
در پروژه MedicalRec ما نياز به يه نفر جهت مشاركت داريم(جايگاه ٧)
Project Title: MedRec: Medical recommender system for image classification without retraining
Github: https://github.com/Ramin1Mousa/MedicalRec
Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence
Impact factor: 20.8
🔸 7- 200$❌
جهت مشارکت می تونید به ایدی بنده پیام بدین.
🧠🧠🧠🧠🧠
@Raminmousa
⭐️ Fast Think-on-Graph: Wider, Deeper and Faster Reasoning of Large Language Model on Knowledge Graph
🖥 Github: https://github.com/dosonleung/fasttog
📕 Paper: https://arxiv.org/abs/2501.14300v1
@Machine_learn
در این پروژه امکان اموزش کامل کد نویسی مدل هم برای کسانی که مشارکت میکنن فراهم
Читать полностью…
📄A Survey of Genetic Programming Applications in Modern Biological Research
📎 Study the paper
@Machine_learn
با عرض سلام نفر ٥ ام از پروژه جديدمون باقي مونده و ٦ جايگاه ديگه پر شدن.
امكان اموزش كامل كار
كدنويسي كار
نحوه جمع اوري داده ها
نگارش مقاله در اين كار وجود داره
Project Title: MedRec: Medical recommender system for image classification without retraining
Github: https://github.com/Ramin1Mousa/MedicalRec
Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence
Impact factor: 20.8
🔺 5- 300$
جهت مشارکت می تونید به ایدی بنده پیام بدین.
@Raminmousa
WILDCHAT-50M: A Deep Dive Into the Role of Synthetic Data in Post-Training
🖥 Github: https://github.com/penfever/wildchat-50m
📕 Paper: https://arxiv.org/abs/2501.18511v1
🧠 Dataset: https://huggingface.co/collections/nyu-dice-lab/wildchat-50m-679a5df2c5967db8ab341ab7
@Machine_learn
DeepSeek LLM: Scaling Open-Source Language Models with Longtermism
Paper: https://arxiv.org/pdf/2401.02954v1.pdf
Code: https://github.com/deepseek-ai/deepseek-llm
Dataset: AlignBench
@Machine_learn
اخرین زمان برای مشارکت در این پروژه تا اخر شب...!
@Raminmousa
با عرض سلام در يكي از پروژه هاي طبقه بندي سرطان پوست نياز به مشاركت داريم. جايگاه نفر سوم خالي مي باشد.
🔸🔻🔸🔻🔸🔻🔻
@Raminmousa
International AI Safety Report
📚 Report
@Machine_learn
How to run 🐋 DeepSeek locally on your Computer
@Machine_learn
💡 Distilabel
▪ GitHub
/channel/deep_learning_proj
JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation
We present JanusFlow, a powerful framework that unifies image understanding and generation in a single model. JanusFlow introduces a minimalist architecture that integrates autoregressive language models with rectified flow, a state-of-the-art method in generative modeling. Our key finding demonstrates that rectified flow can be straightforwardly trained within the large language model framework, eliminating the need for complex architectural modifications. To further improve the performance of our unified model, we adopt two key strategies: (i) decoupling the understanding and generation encoders, and (ii) aligning their representations during unified training. Extensive experiments show that JanusFlow achieves comparable or superior performance to specialized models in their respective domains, while significantly outperforming existing unified approaches across standard benchmarks. This work represents a step toward more efficient and versatile vision-language models.
Paper: https://arxiv.org/pdf/2411.07975v1.pdf
Code: https://github.com/deepseek-ai/janus
Datasets: GQA MMBench MM-Vet SEED-Bench
@Machine_learn
ChatGPT Cheat Sheet for Business - DataCamp
@Machine_learn
🌟 SmolVLM:
SmolVLM -
⭐️ smolervlm: https://huggingface.co/blog/smolervlm
Model: https://huggingface.co/collections/HuggingFaceTB/smolvlm-256m-and-500m-6791fafc5bb0ab8acc960fb0
@Machine_learn
Foundations of Geometry. DAVID HILBERT, PH. D.
📚 Book
@Machine_learn
Discrete Matematics and applications
🔗 link
@Machine_learn
با عرض سلام پروژه MedicalRec تنها نفر ٤ ام باقي مونده و امشب استارت کار میباشد.
🫥🫥🫥🫥
هدف اصلی این پروژه اموزش یک مدل پیشنهاد دهنده ی مدل برای مسائله طبقه بندی تصاویر پزشکی میباشد که از اموزش مجدد مدل ها جلوگیری میکند. این مسائله با جنبه جلوگیری از مصرف انرژی اموزشی و زمان اموزش مدل ها ارائه می شود. برای این منظور ۵۰۰۰ مقاله در این زمینه جمع اوری شده است. جزئیات بیشتر در لینک گیت قرار دارد.
Project Title: MedRec: Medical recommender system for image classification without retraining
Github: https://github.com/Ramin1Mousa/MedicalRec
Journal: IEEE Transactions on Pattern Analysis and Machine Intelligence
Impact factor: 20.8
🔹 2- 600$❌
🔺 3- 500$❌
💠 4- 400$✅
🔺 5- 300$▫️
🔹 6- 200$❌
🔸 7- 200$❌
جهت مشارکت می تونید به ایدی بنده پیام بدین.
🧠🧠🧠🧠🧠
@Raminmousa
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