现已上线！2025 年 Telegram 研究 — 年度关键洞察 
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 40 072 名订阅者，在 技术与应用 类别中位列第 3 398，并在 叙利亚 地区排名第 232 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 40 072 名订阅者。
根据 23 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 379，过去 24 小时变化为 30，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 1.92%。内容发布后 24 小时内通常能获得 1.16% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 770 次浏览，首日通常累积 466 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 24 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。
40 072
订阅者
+3024 小时
+337 天
+37930 天
帖子存档
40 089
📌 An End-to-End Guide to Beautifying Your Open-Source Repo with Agentic AI
🗂 Category: LLM APPLICATIONS
🕒 Date: 2026-02-20 | ⏱️ Read time: 17 min read
The guide to automated improvement of scientific and industrial repositories using open-source AI agents
#DataScience #AI #Python
40 089
📌 Donkeys, Not Unicorns
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2026-02-20 | ⏱️ Read time: 8 min read
The New Rules of Entrepreneurship in the Era of Commoditized Magic
#DataScience #AI #Python
40 089
📌 AI in Multiple GPUs: How GPUs Communicate
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2026-02-19 | ⏱️ Read time: 5 min read
A deep dive into the hardware infrastructure that enables multi-GPU communication for AI workloads
#DataScience #AI #Python
40 089
📌 AlpamayoR1: Large Causal Reasoning Models for Autonomous Driving
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2026-02-19 | ⏱️ Read time: 9 min read
All you need to know about Chain of Causation reasoning and the current state of…
#DataScience #AI #Python
40 089
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40 089
📌 Understanding the Chi-Square Test Beyond the Formula
🗂 Category: STATISTICS
🕒 Date: 2026-02-19 | ⏱️ Read time: 17 min read
How categorical data becomes statistical evidence.
#DataScience #AI #Python
40 089
📌 The Missing Curriculum: Essential Concepts For Data Scientists in the Age of AI Coding Agents
🗂 Category: PROGRAMMING
🕒 Date: 2026-02-19 | ⏱️ Read time: 13 min read
AI can write the code, but you have to steer the ship. Master the knowledge…
#DataScience #AI #Python
40 089
📌 Agentic AI for Modern Deep Learning Experimentation
🗂 Category: AGENTIC AI
🕒 Date: 2026-02-18 | ⏱️ Read time: 14 min read
Stop babysitting training runs. Start shipping research. Autonomous experiment management built for/by deep learning engineers.
#DataScience #AI #Python
40 089
📌 Why Every Analytics Engineer Needs to Understand Data Architecture
🗂 Category: DATA ENGINEERING
🕒 Date: 2026-02-18 | ⏱️ Read time: 11 min read
Get the data architecture right, and everything else becomes easier. I know it sounds simple,…
#DataScience #AI #Python
40 089
📌 Building Cost-Efficient Agentic RAG on Long-Text Documents in SQL Tables
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2026-02-18 | ⏱️ Read time: 13 min read
Designing a hybrid SQL + vector retrieval system without schema changes, data migration, or performance…
#DataScience #AI #Python
40 089
📌 Can AI Solve Failures in Your Supply Chain?
🗂 Category: AGENTIC AI
🕒 Date: 2026-02-18 | ⏱️ Read time: 16 min read
When your warehouse and transportation teams blame each other for late deliveries, who’s right? We…
#DataScience #AI #Python
40 089
📌 Use OpenClaw to Make a Personal AI Assistant
🗂 Category: AGENTIC AI
🕒 Date: 2026-02-17 | ⏱️ Read time: 10 min read
Learn how to set up OpenClaw as a personalized AI agent
#DataScience #AI #Python
40 089
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40 089
📌 Advance Planning for AI Project Evaluation
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2026-02-17 | ⏱️ Read time: 7 min read
The work to do before the work begins
#DataScience #AI #Python
40 089
📌 Iron Triangles: Powerful Tools for Analyzing Trade-Offs in AI Product Development
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2026-02-17 | ⏱️ Read time: 9 min read
Conceptual overview and practical guidance
#DataScience #AI #Python
40 089
Repost from Machine Learning with Python
🔖 An excellent resource for learning about neural networks
We're sharing a cool resource for learning about neural networks, offering clear, step-by-step instruction with dynamic visualizations and easy-to-understand explanations.
In addition, you'll find many other useful materials on machine learning on the site.
Find and use it — https://mlu-explain.github.io/neural-networks/
tags: #AI #ML #PYTHON
➡ @CODEPROGRAMMER
40 089
📌 Building a LangGraph Agent from Scratch
🗂 Category: AGENTIC AI
🕒 Date: 2026-02-17 | ⏱️ Read time: 10 min read
Everything you need to know to get started
#DataScience #AI #Python
40 089
📌 The Strangest Bottleneck in Modern LLMs
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2026-02-16 | ⏱️ Read time: 11 min read
Why insanely fast GPUs still can’t make LLMs feel instant
#DataScience #AI #Python
