Machine Learning
前往频道在 Telegram
Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho
显示更多📈 Telegram 频道 Machine Learning 的分析概览
频道 Machine Learning (@machinelearning9) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 40 150 名订阅者,在 技术与应用 类别中位列第 3 364,并在 叙利亚 地区排名第 227 位。
📊 受众指标与增长动态
自 невідомо 创建以来,项目保持高速增长,吸引了 40 150 名订阅者。
根据 27 六月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 412,过去 24 小时变化为 5,整体触达仍然可观。
- 认证状态: 未认证
- 互动率 (ER): 平均受众互动率为 1.96%。内容发布后 24 小时内通常能获得 1.89% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 785 次浏览,首日通常累积 760 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 2。
- 主题关注点: 内容集中在 distance, insidead, gpu, learning, degree 等核心主题上。
📝 描述与内容策略
作者将该频道定位为表达主观观点的平台:
“Real Machine Learning — simple, practical, and built on experience.
Learn step by step with clear explanations and working code.
Admin: @HusseinSheikho || @Hussein_Sheikho”
凭借高频更新(最新数据采集于 28 六月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 技术与应用 类别中的关键影响点。
40 150
订阅者
+524 小时
+1067 天
+41230 天
帖子存档
40 146
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📌 How to Build An AI Agent with Function Calling and GPT-5
🗂 Category: AGENTIC AI
🕒 Date: 2025-10-20 | ⏱️ Read time: 15 min read
How an AI agent works: a step-by-step guide
40 146
🤖🧠 Master Machine Learning with Stanford’s CS229 Cheatsheets: The Ultimate Learning Resource
🗓️ 21 Oct 2025
📚 AI News & Trends
Machine learning is one of the most transformative fields in technology today. From powering recommendation systems to enabling self-driving cars, machine learning is at the core of modern artificial intelligence. However, mastering its vast concepts, equations and algorithms can be overwhelming especially for beginners and busy professionals. That’s where the Stanford CS229 Machine Learning Cheatsheets ...
40 146
🤖🧠 Master Machine Learning with Stanford’s CS229 Cheatsheets: The Ultimate Learning Resource
🗓️ 21 Oct 2025
📚 AI News & Trends
Machine learning is one of the most transformative fields in technology today. From powering recommendation systems to enabling self-driving cars, machine learning is at the core of modern artificial intelligence. However, mastering its vast concepts, equations and algorithms can be overwhelming especially for beginners and busy professionals. That’s where the Stanford CS229 Machine Learning Cheatsheets ...
40 146
🤖🧠 The Art of Scaling Reinforcement Learning Compute for LLMs: Top Insights from Meta, UT Austin and Harvard University
🗓️ 21 Oct 2025
📚 AI News & Trends
As Large Language Models (LLMs) continue to redefine artificial intelligence, a new research breakthrough has emerged from Meta, The University of Texas at Austin, University College London, UC Berkeley, Harvard University and Periodic Labs. Their paper, titled “The Art of Scaling Reinforcement Learning Compute for LLMs,” introduces a transformative framework for understanding how reinforcement learning ...
#ReinforcementLearning #LLMs #AIResearch #Meta #UTAustin #HarvardUniversity
40 146
🤖🧠 The Art of Scaling Reinforcement Learning Compute for LLMs: Top Insights from Meta, UT Austin and Harvard University
🗓️ 21 Oct 2025
📚 AI News & Trends
As Large Language Models (LLMs) continue to redefine artificial intelligence, a new research breakthrough has emerged from Meta, The University of Texas at Austin, University College London, UC Berkeley, Harvard University and Periodic Labs. Their paper, titled “The Art of Scaling Reinforcement Learning Compute for LLMs,” introduces a transformative framework for understanding how reinforcement learning ...
#ReinforcementLearning #LLMs #AIResearch #Meta #UTAustin #HarvardUniversity
40 146
📌 Implementing the Fourier Transform Numerically in Python: A Step-by-Step Guide
🗂 Category: MATH
🕒 Date: 2025-10-21 | ⏱️ Read time: 19 min read
What if the FFT functions in NumPy and SciPy don’t actually compute the Fourier transform…
40 146
📌 Implementing the Fourier Transform Numerically in Python: A Step-by-Step Guide
🗂 Category: MATH
🕒 Date: 2025-10-21 | ⏱️ Read time: 19 min read
What if the FFT functions in NumPy and SciPy don’t actually compute the Fourier transform…
40 146
🤖🧠 DeepSeek-OCR: Redefining Document Understanding Through Optical Context Compression
🗓️ 21 Oct 2025
📚 AI News & Trends
In the age of large language models (LLMs) and vision-language models (VLMs), handling long and complex textual data efficiently remains a massive challenge. Traditional models struggle with processing extended contexts because the computational cost increases quadratically with sequence length. To overcome this, researchers from DeepSeek-AI have introduced a groundbreaking approach – DeepSeek-OCR, a model that ...
40 146
🤖🧠 Wan 2.1: Alibaba’s Open-Source Revolution in Video Generation
🗓️ 21 Oct 2025
📚 AI News & Trends
The landscape of artificial intelligence has been evolving rapidly, especially in the domain of video generation. Since OpenAI unveiled Sora in 2024, the world has witnessed an explosive surge in research and innovation within generative AI. However, most of these cutting-edge tools remained closed-source limiting transparency and accessibility. Recognizing this gap, Alibaba Group introduced Wan, ...
#Alibaba #Wan2.1 #VideoGeneration #GenerativeAI #OpenSource #ArtificialIntelligence
40 146
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40 146
🤖🧠 Top 30 More Retro Bollywood Diwali Portrait Prompts for Women Using Gemini AI – Part 2
🗓️ 20 Oct 2025
📚 AI News & Trends
The Diwali celebrations continue and so does the nostalgia! After the huge buzz around our Top 20 Retro Bollywood Diwali Portrait Ideas, we’re back with Part 2 featuring prompts 21 to 50 curated to help you create even more magical, cinematic AI portraits using Google Gemini AI. If you loved the 90s-style Diwali aesthetics shimmering ...
40 146
🤖🧠 PaddleOCR-VL: Redefining Multilingual Document Parsing with a 0.9B Vision-Language Model
🗓️ 20 Oct 2025
📚 AI News & Trends
In an era where information is predominantly digital, the ability to extract, interpret and organize data from documents is crucial. From invoices and research papers to multilingual contracts and handwritten notes, document parsing stands at the intersection of vision and language. Traditional Optical Character Recognition (OCR) systems have made impressive strides but they often fall ...
#PaddleOCR-VL #Multilingual #DocumentParsing #VisionLanguageModel #OCR #AI
40 146
🤖🧠 PaddleOCR-VL: Redefining Multilingual Document Parsing with a 0.9B Vision-Language Model
🗓️ 20 Oct 2025
📚 AI News & Trends
In an era where information is predominantly digital, the ability to extract, interpret and organize data from documents is crucial. From invoices and research papers to multilingual contracts and handwritten notes, document parsing stands at the intersection of vision and language. Traditional Optical Character Recognition (OCR) systems have made impressive strides but they often fall ...
#PaddleOCR-VL #Multilingual #DocumentParsing #VisionLanguageModel #OCR #AI
40 146
🤖🧠 NanoChat: The Best ChatGPT That $100 Can Buy
🗓️ 20 Oct 2025
📚 AI News & Trends
In a world dominated by billion-dollar AI models like GPT-4 and Claude 3, it’s refreshing to see a minimalist, open-source alternative that puts the power of Large Language Models (LLMs) back into the hands of hackers, researchers and enthusiasts. Enter NanoChat – an end-to-end, full-stack implementation of a ChatGPT-style AI chatbot developed by Andrej Karpathy, ...
#NanoChat #ChatGPT #AI #LargeLanguageModels #OpenSource #AndrejKarpathy
40 146
🤖🧠 NanoChat: The Best ChatGPT That $100 Can Buy
🗓️ 20 Oct 2025
📚 AI News & Trends
In a world dominated by billion-dollar AI models like GPT-4 and Claude 3, it’s refreshing to see a minimalist, open-source alternative that puts the power of Large Language Models (LLMs) back into the hands of hackers, researchers and enthusiasts. Enter NanoChat – an end-to-end, full-stack implementation of a ChatGPT-style AI chatbot developed by Andrej Karpathy, ...
#NanoChat #ChatGPT #AI #LargeLanguageModels #OpenSource #AndrejKarpathy
40 146
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40 146
📌 Building a Data Engineering Center of Excellence
🗂 Category: DATA ENGINEERING
🕒 Date: 2025-02-13 | ⏱️ Read time: 11 min read
As data continues to grow in importance and become more complex, the need for skilled…
现已上线!2025 年 Telegram 研究 — 年度关键洞察 
