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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网络:Machine Learning with Python 叙利亚232 技术与应用3 398...

📈 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

770

帖子浏览量

~ 46624 小时

~ 62048 小时

1.92%

参与率

~ 3

每日帖子数

Ads index

beta

帖子存档

40 085

📌 The Machine Learning Lessons I’ve Learned This Month 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-03-02 | ⏱️ Read time: 6 min read February 2026: exchange with others, documentation, and MLOps #DataScience #AI #Python

40 085

Repost from Machine Learning with Python

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📌 YOLOv3 Paper Walkthrough: Even Better, But Not That Much 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2026-03-02 | ⏱️ Read time: 24 min read A PyTorch implementation on the YOLOv3 architecture from scratch #DataScience #AI #Python

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📌 Exciting Changes Are Coming to the TDS Author Payment Program 🗂 Category: WRITING 🕒 Date: 2026-03-02 | ⏱️ Read time: 2 min read Authors can now benefit from updated earning tiers and a higher article cap #DataScience #AI #Python

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📌 Context Engineering as Your Competitive Edge 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-03-01 | ⏱️ Read time: 13 min read If you have both unique domain expertise and know how to make it usable to… #DataScience #AI #Python

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📌 Zero-Waste Agentic RAG: Designing Caching Architectures to Minimize Latency and LLM Costs at Scale 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-03-01 | ⏱️ Read time: 19 min read Reducing LLM costs by 30% with validation-aware, multi-tier caching #DataScience #AI #Python

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📌 Scaling ML Inference on Databricks: Liquid or Partitioned? Salted or Not? 🗂 Category: DATA ENGINEERING 🕒 Date: 2026-02-28 | ⏱️ Read time: 11 min read A case study on techniques to maximize your clusters #DataScience #AI #Python

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📌 Claude Skills and Subagents: Escaping the Prompt Engineering Hamster Wheel 🗂 Category: AGENTIC AI 🕒 Date: 2026-02-28 | ⏱️ Read time: 17 min read How reusable, lazy-loaded instructions solve the context bloat problem in AI-assisted development. #DataScience #AI #Python

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📌 The Gap Between Junior and Senior Data Scientists Isn’t Code 🗂 Category: DATA SCIENCE 🕒 Date: 2026-02-27 | ⏱️ Read time: 6 min read Why my obsession with complex algorithms was actually holding my career back. #DataScience #AI #Python

40 085

📌 Generative AI, Discriminative Human 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2026-02-27 | ⏱️ Read time: 14 min read How to think critically about AI in an ocean of hype #DataScience #AI #Python

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📌 Stop Asking if a Model Is Interpretable 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2026-02-27 | ⏱️ Read time: 6 min read Start asking what question the explanation should answer. #DataScience #AI #Python

40 085

📌 Coding the Pong Game from Scratch in Python 🗂 Category: PROGRAMMING 🕒 Date: 2026-02-27 | ⏱️ Read time: 18 min read Implementing the classic Pong game in Python using OOP and Turtle #DataScience #AI #Python

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📌 Take a Deep Dive into Filtering in DAX 🗂 Category: DATA ANALYSIS 🕒 Date: 2026-02-26 | ⏱️ Read time: 13 min read Have you ever wondered what happens when you apply a filter in a DAX expression?… #DataScience #AI #Python

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📌 Designing Data and AI Systems That Hold Up in Production 🗂 Category: AUTHOR SPOTLIGHTS 🕒 Date: 2026-02-26 | ⏱️ Read time: 6 min read A system-level perspective on architecture, agents, and responsible scale #DataScience #AI #Python

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Repost from Machine Learning with Python

Free access to over 40 courses https://lve.to/jwxfnss0yi

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📌 Detecting and Editing Visual Objects with Gemini 🗂 Category: LLM APPLICATIONS 🕒 Date: 2026-02-26 | ⏱️ Read time: 34 min read A practical guide to identifying, restoring, and transforming elements within your images #DataScience #AI #Python

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📌 A Generalizable MARL-LP Approach for Scheduling in Logistics 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-02-26 | ⏱️ Read time: 17 min read Part 1. Hybrid Solution for Dynamic Vehicle Routing — Context and Architecture #DataScience #AI #Python

40 085

📌 Breaking the Host Memory Bottleneck: How Peer Direct Transformed Gaudi’s Cloud Performance 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2026-02-25 | ⏱️ Read time: 9 min read Engineering RDMA-like performance over cloud host NICs using libfabric, DMA-BUF, and HCCL to restore distributed… #DataScience #AI #Python

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📌 Scaling Feature Engineering Pipelines with Feast and Ray 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-02-25 | ⏱️ Read time: 11 min read Utilizing feature stores like Feast and distributed compute frameworks like Ray in production machine learning systems #DataScience #AI #Python