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227 技术与应用3 343...

📈 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 40 265 名订阅者，在 技术与应用 类别中位列第 3 343，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 40 265 名订阅者。

根据 06 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 336，过去 24 小时变化为 -4，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 2.25%。内容发布后 24 小时内通常能获得 1.88% 的反应，占订阅者总量。
帖子覆盖： 每篇帖子平均可获得 906 次浏览，首日通常累积 758 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 07 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。

40 265

订阅者

-424 小时

+917 天

+33630 天

906

帖子浏览量

~ 75824 小时

~ 1 03748 小时

2.25%

参与率

~ 3

每日帖子数

Ads index

beta

帖子存档

40 265

I spent months trying every way to grow my Telegram channel. Nothing worked… until I found this secret tool. It finds advertisers and subscribers for you — and even pays you! Now my channel is earning while I sleep. Want the same results? Try it here #ad InsideAds .

40 265

📌 Statistical Learnability of Strategic Linear Classifiers: A Proof Walkthrough 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-01-08 | ⏱️ Read time: 19 min read With the help of an intricate geometric construction, we can prove that instance-wise cost functions…

40 265

📌 Advanced SQL Techniques for Unstructured Data Handling 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-08 | ⏱️ Read time: 7 min read Everything you need to know to get started with text mining

40 265

📌 Missing Data in Time-Series? Machine Learning Techniques (Part 2) 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-01-08 | ⏱️ Read time: 12 min read Using Clustering Algorithms to Handle Missing Time-Series Data

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📌 Speed Up PyTorch With Custom Kernels. But It Gets Progressively Darker 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-01-09 | ⏱️ Read time: 5 min read We’ll begin with torch.compile, move on to writing a custom Triton kernel, and finally dive…

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📌 Jingle Bells and Statistical Tests 🗂 Category: STATISTICS 🕒 Date: 2024-12-25 | ⏱️ Read time: 8 min read Data Types, Hypotheses and Statistical Tests That Fit Them with Festive Christmas Market Examples

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📌 Understanding When and How to Implement FastAPI Middleware (Examples and Use Cases) 🗂 Category: DATA SCIENCE 🕒 Date: 2024-12-25 | ⏱️ Read time: 4 min read Supercharge Your FastAPI with Middleware: Practical Use Cases and Examples

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📌 Training LLM, from Scratch, in Rust 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-12-26 | ⏱️ Read time: 16 min read In this companion article, I’ll show my implementation for training from scratch a GPT-like model,…

40 265

📌 Calculating a linear extrapolation (or Trend) in DAX 🗂 Category: 🕒 Date: 2024-12-26 | ⏱️ Read time: 10 min read In DAX there is no built-in method to calculate a Trend. Therefore we must do…

40 265

📌 Your Company Needs Small Language Models 🗂 Category: CHATGPT 🕒 Date: 2024-12-26 | ⏱️ Read time: 15 min read When specialized models outperform general-purpose models

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📌 Linearizing Attention 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-12-26 | ⏱️ Read time: 8 min read Breaking the Quadratic Barrier: Modern Alternatives to Softmax Attention

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📌 How Neural Networks Learn: A Probabilistic Viewpoint 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-12-26 | ⏱️ Read time: 8 min read Understanding Loss Functions in Training Neural Networks

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📌 Track Computer Vision Experiments with MLflow 🗂 Category: 🕒 Date: 2024-12-26 | ⏱️ Read time: 10 min read Discover how to set up an efficient MLflow environment to track your experiments, compare and…

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📌 Lessons from COVID-19: Why Probability Distributions Matter 🗂 Category: COVID-19 🕒 Date: 2024-12-27 | ⏱️ Read time: 13 min read Understanding Distributions with Extremes: Probability for Data Science Series (END)

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📌 Understanding the Optimization Process Pipeline in Linear Programming 🗂 Category: 🕒 Date: 2024-12-27 | ⏱️ Read time: 8 min read An introduction to the backend and frontend processes in linear programming, including the mathematical programming…

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📌 Master Bots Before Starting with AI Agents: Simple Steps to Create a Mastodon Bot with Python 🗂 Category: PROGRAMMING 🕒 Date: 2024-12-27 | ⏱️ Read time: 13 min read I recently published a post on Mastodon that was shared by six other accounts within…

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📌 Measuring Cross-Product Adoption Using dbt_set_similarity 🗂 Category: SQL 🕒 Date: 2024-12-28 | ⏱️ Read time: 5 min read Enhancing cross-product insights within dbt workflows

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📌 Deep Dive into Multithreading, Multiprocessing, and Asyncio 🗂 Category: 🕒 Date: 2024-12-28 | ⏱️ Read time: 10 min read How to choose the right concurrency model

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📌 Superposition: What Makes it Difficult to Explain Neural Network 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-12-29 | ⏱️ Read time: 7 min read When there are more features than model dimensions