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Machine Learning

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

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📈 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 40 202 名订阅者,在 技术与应用 类别中位列第 3 365,并在 叙利亚 地区排名第 227

📊 受众指标与增长动态

невідомо 创建以来,项目保持高速增长,吸引了 40 202 名订阅者。

根据 02 七月, 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 343,过去 24 小时变化为 10,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 1.99%。内容发布后 24 小时内通常能获得 2.28% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 800 次浏览,首日通常累积 915 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 3
  • 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 03 七月, 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。

40 202
订阅者
+1024 小时
+837
+34330
帖子存档
📌 Python QuickStart for People Learning AI 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-08 | ⏱️ Read time: 15 min read A begin
📌 Python QuickStart for People Learning AI 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-08 | ⏱️ Read time: 15 min read A beginner-friendly guide

📌 Galactic Distances 🗂 Category: 🕒 Date: 2024-09-08 | ⏱️ Read time: 18 min read How Far Are We from Alien Civilizations? (
📌 Galactic Distances 🗂 Category: 🕒 Date: 2024-09-08 | ⏱️ Read time: 18 min read How Far Are We from Alien Civilizations? (Part 4 of the Drake Equation Series)

📌 Are We Alone? 🗂 Category: SCIENCE AND TECHNOLOGY 🕒 Date: 2024-09-08 | ⏱️ Read time: 12 min read The Real Odds of Encount
📌 Are We Alone? 🗂 Category: SCIENCE AND TECHNOLOGY 🕒 Date: 2024-09-08 | ⏱️ Read time: 12 min read The Real Odds of Encountering Alien Life (Part 5 of the Drake Equation Series)

📌 Automate Video Chaptering with LLMs and TF-IDF 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-09-09 | ⏱️ Read time: 14 m
📌 Automate Video Chaptering with LLMs and TF-IDF 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-09-09 | ⏱️ Read time: 14 min read Transform raw transcripts into well-structured documents

📌 Benchmarking Hallucination Detection Methods in RAG 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-09-09 | ⏱️ Read time:
📌 Benchmarking Hallucination Detection Methods in RAG 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-09-09 | ⏱️ Read time: 11 min read Evaluating methods to enhance reliability in LLM-generated responses.

📌 Does Semi-Supervised Learning Help to Train Better Models? 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-09-09 | ⏱️ Read tim
📌 Does Semi-Supervised Learning Help to Train Better Models? 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-09-09 | ⏱️ Read time: 8 min read Evaluating how semi-supervised learning can leverage unlabeled data

📌 Is Multi-Collinearity Destroying Your Causal Inferences In Marketing Mix Modelling? 🗂 Category: DATA SCIENCE 🕒 Date: 202
📌 Is Multi-Collinearity Destroying Your Causal Inferences In Marketing Mix Modelling? 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-10 | ⏱️ Read time: 18 min read Causal AI, exploring the integration of causal reasoning into machine learning

📌 MobileNetV2 Paper Walkthrough: The Smarter Tiny Giant 🗂 Category: DEEP LEARNING 🕒 Date: 2025-10-03 | ⏱️ Read time: 28 mi
📌 MobileNetV2 Paper Walkthrough: The Smarter Tiny Giant 🗂 Category: DEEP LEARNING 🕒 Date: 2025-10-03 | ⏱️ Read time: 28 min read Understanding and implementing MobileNetV2 with PyTorch  — the next generation of MobileNetV1

📌 Build a Data Dashboard Using HTML, CSS, and JavaScript 🗂 Category: PROGRAMMING 🕒 Date: 2025-10-03 | ⏱️ Read time: 14 min
📌 Build a Data Dashboard Using HTML, CSS, and JavaScript 🗂 Category: PROGRAMMING 🕒 Date: 2025-10-03 | ⏱️ Read time: 14 min read A framework-free guide for Python programmers

📌 Introducing NumPy, Part 3: Manipulating Arrays 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-15 | ⏱️ Read time: 7 min read Sh
📌 Introducing NumPy, Part 3: Manipulating Arrays 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-15 | ⏱️ Read time: 7 min read Shaping, transposing, joining, and splitting arrays

soon

I used to think trading was all about luck… until I saw what happens when you apply actual discipline. My P&L chart never loo
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Nobody believed I could boost my speed with just one hidden tech trick—until I did. Now, my Android feels like new and my iPh
Nobody believed I could boost my speed with just one hidden tech trick—until I did. Now, my Android feels like new and my iPhone unlocks features I never expected. The secret? Find out before everyone else — only revealed here! #ad InsideAds

No one tells you this, but sometimes you need to disappear for 24 hours to finally find yourself. Could you survive it? Every
No one tells you this, but sometimes you need to disappear for 24 hours to finally find yourself. Could you survive it? Everyone talks about problems and pain… but what if you just walked away—for a day? Find out the answer here — dare to try? #ad InsideAds

📌 Key Insights for Teaching AI Agents to Remember 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-09-10 | ⏱️ Read time: 2
📌 Key Insights for Teaching AI Agents to Remember 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-09-10 | ⏱️ Read time: 20 min read Recommendations on building robust memory capabilities based on experimentation with Autogen’s “Teachable Agents”

📌 The Art of Asking Questions for Engineers 🗂 Category: BUSINESS 🕒 Date: 2024-09-10 | ⏱️ Read time: 6 min read A Guideline
📌 The Art of Asking Questions for Engineers 🗂 Category: BUSINESS 🕒 Date: 2024-09-10 | ⏱️ Read time: 6 min read A Guideline for Asking Impactful Questions

📌 Practical Introduction to Polars 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-10 | ⏱️ Read time: 13 min read Hands-on guide
📌 Practical Introduction to Polars 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-10 | ⏱️ Read time: 13 min read Hands-on guide with side-by-side examples in Pandas

📌 Logistic Regression, Explained: A Visual Guide with Code Examples for Beginners 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09
📌 Logistic Regression, Explained: A Visual Guide with Code Examples for Beginners 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-10 | ⏱️ Read time: 9 min read Finding the perfect weights to fit the data in