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 40 100 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 40 100 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。

40 100

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

40 105

📌 Achieving 5x Agentic Coding Performance with Few-Shot Prompting 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-01-23 | ⏱️ Read time: 9 min read Learn to leverage few-shot prompting to increase your LLMs performance #DataScience #AI #Python

40 105

📌 Optimizing Data Transfer in Distributed AI/ML Training Workloads 🗂 Category: DATA ENGINEERING 🕒 Date: 2026-01-23 | ⏱️ Read time: 15 min read A deep dive on data transfer bottlenecks, their identification, and their resolution with the help… #DataScience #AI #Python

40 105

📌 What Other Industries Can Learn from Healthcare’s Knowledge Graphs 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-22 | ⏱️ Read time: 11 min read How shared meaning, evidence, and standards create durable semantic infrastructure #DataScience #AI #Python

40 105

📌 Stop Writing Messy Boolean Masks: 10 Elegant Ways to Filter Pandas DataFrames 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-22 | ⏱️ Read time: 7 min read Master the art of readable, high-performance data selection using .query(), .isin(), and advanced vectorized logic. #DataScience #AI #Python

40 105

📌 Why SaaS Product Management Is the Best Domain for Data-Driven Professionals in 2026 🗂 Category: PRODUCT MANAGEMENT 🕒 Date: 2026-01-22 | ⏱️ Read time: 14 min read How I use analytics, automation, and AI to build better SaaS #DataScience #AI #Python

40 105

📌 Evaluating Multi-Step LLM-Generated Content: Why Customer Journeys Require Structural Metrics 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-01-22 | ⏱️ Read time: 13 min read How to evaluate goal-oriented content designed to build engagement and deliver business results, and why… #DataScience #AI #Python

40 105

📌 A Case for the T-statistic 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-21 | ⏱️ Read time: 21 min read And how it compares to the run-of-the-mill z-score #DataScience #AI #Python

40 105

Guide to AI Coding Agents & Assistants: How to Choose the Right One There are now so many AI tools for coding that it can be confusing to know which one to pick. Some act as simple helpers (Assistant), while others can do the work for you (Agent). This guide breaks down the top AI coding tools that you should be aware of. We will look at what they do, who they are for, and how much they cost. Read: https://habr.com/en/articles/979402/ https://t.me/DataScienceM

40 105

📌 Building a Self-Healing Data Pipeline That Fixes Its Own Python Errors 🗂 Category: LLM APPLICATIONS 🕒 Date: 2026-01-21 | ⏱️ Read time: 8 min read How I built a self-healing pipeline that automatically fixes bad CSVs, schema changes, and weird… #DataScience #AI #Python

40 105

📌 If You Want to Become a Data Scientist in 2026, Do This 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-21 | ⏱️ Read time: 10 min read Learn from my mistakes and fast track your data science career #DataScience #AI #Python

40 105

📌 Google Trends is Misleading You: How to Do Machine Learning with Google Trends Data 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-21 | ⏱️ Read time: 11 min read Google Trends is one of the most widely used tools for analysing human behaviour at… #DataScience #AI #Python

40 105

Repost from Github Top Repositories

🔥 Trending Repository: Data-Science-For-Beginners 📝 Description: 10 Weeks, 20 Lessons, Data Science for All! 🔗 Repository URL: https://github.com/microsoft/Data-Science-For-Beginners 📖 Readme: https://github.com/microsoft/Data-Science-For-Beginners#readme 📊 Statistics: 🌟 Stars: 31.9K stars 👀 Watchers: 513 🍴 Forks: 6.8K forks 💻 Programming Languages: Jupyter Notebook 🏷️ Related Topics:

#python #data_science #pandas #data_visualization #data_analysis #microsoft_for_beginners

================================== 🧠 By: https://t.me/DataScienceM

40 105

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40 105

📌 How to Perform Large Code Refactors in Cursor 🗂 Category: AGENTIC AI 🕒 Date: 2026-01-20 | ⏱️ Read time: 10 min read Learn how to perform code refactoring with LLMs #DataScience #AI #Python

40 105

📌 Does Calendar-Based Time-Intelligence Change Custom Logic? 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-20 | ⏱️ Read time: 8 min read Let’s look at calculating the moving average over time #DataScience #AI #Python

40 105

📌 Why Package Installs Are Slow (And How to Fix It) 🗂 Category: DATA ENGINEERING 🕒 Date: 2026-01-20 | ⏱️ Read time: 7 min read How sharded indexing patterns solve a scaling problem in package management #DataScience #AI #Python

40 105

📌 You Probably Don’t Need a Vector Database for Your RAG — Yet 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-01-20 | ⏱️ Read time: 14 min read Numpy or SciKit-Learn might meet all your retrieval needs #DataScience #AI #Python

40 105

📌 Time Series Isn’t Enough: How Graph Neural Networks Change Demand Forecasting 🗂 Category: DATA SCIENCE 🕒 Date: 2026-01-19 | ⏱️ Read time: 11 min read Why modeling SKUs as a network reveals what traditional forecasts miss #DataScience #AI #Python

40 105

📌 Using Local LLMs to Discover High-Performance Algorithms 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-01-19 | ⏱️ Read time: 10 min read How I used open-source models to explore new frontiers in efficient code generation, using my… #DataScience #AI #Python

40 105

📌 Bridging the Gap Between Research and Readability with Marco Hening Tallarico 🗂 Category: AUTHOR SPOTLIGHTS 🕒 Date: 2026-01-19 | ⏱️ Read time: 6 min read Diluting complex research, spotting silent data leaks, and why the best way to learn is… #DataScience #AI #Python