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3 364...

📈 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 40 150 名订阅者，在 技术与应用 类别中位列第 3 364，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 40 150 名订阅者。

根据 27 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 412，过去 24 小时变化为 5，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 1.96%。内容发布后 24 小时内通常能获得 1.89% 的反应，占订阅者总量。
帖子覆盖： 每篇帖子平均可获得 785 次浏览，首日通常累积 760 次浏览。
互动与反馈： 受众积极参与，单帖平均反应数为 2。
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 28 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。

40 150

订阅者

+524 小时

+1067 天

+41230 天

785

帖子浏览量

~ 76024 小时

~ 1 06948 小时

1.96%

参与率

~ 3

每日帖子数

Ads index

beta

帖子存档

40 151

📌 Acquire Customers with Ecommerce Data Science 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-05 | ⏱️ Read time: 7 min read Data informed strategies help ecommerce businesses overcome advertising challenges

40 151

📌 Cross-validation with XGBoost – Enhancing Customer Churn Classification with Tidymodels 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-06 | ⏱️ Read time: 6 min read Step-by-step guide to implementing cross-validation, feature engineering, and model evaluation with XGBoost in Tidymodels

40 151

📌 PAGA Explained: Graphical Abstractions of Single-Cell Data 🗂 Category: DATA VISUALIZATION 🕒 Date: 2024-06-06 | ⏱️ Read time: 7 min read How a broader view of data can give us insights to its deeper meaning.

40 151

📌 My 30-Day Map Challenge 2023 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-06 | ⏱️ Read time: 9 min read An overview of selected map topics and algorithms

40 151

📌 Multilingual RAG, Algorithmic Thinking, Outlier Detection, and Other Problem-Solving Highlights 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-06 | ⏱️ Read time: 4 min read Our weekly selection of must-read Editors’ Picks and original features

40 151

📌 SageMaker vs Vertex AI for Model Inference 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-06-06 | ⏱️ Read time: 14 min read Comparing the AWS and GCP fully-managed services for ML workflows

40 151

📌 From Code to Insights: Software Engineering Best Practices for Data Analysts 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-06 | ⏱️ Read time: 20 min read Top 10 engineering lessons every data analyst should know

40 151

📌 Applied LLM Quantisation with AWS Sagemaker | Analytics.gov 🗂 Category: 🕒 Date: 2024-06-07 | ⏱️ Read time: 19 min read Host production-ready LLMs endpoints at twice the speed but one fifth the cost.

40 151

📌 How LLMs Think 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-06-07 | ⏱️ Read time: 11 min read Research paper in pills: “Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet”

40 151

📌 YOLO – By Hand 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-06-07 | ⏱️ Read time: 6 min read A breakdown of the math within YOLO

40 151

📌 Fraud Prediction with Machine Learning in the Financial Industry: A Data Scientist’s Experience 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-06-07 | ⏱️ Read time: 6 min read Insights and experiences from a data scientist on the frontlines

40 151

📌 Automating Prompt Engineering with DSPy and Haystack 🗂 Category: 🕒 Date: 2024-06-07 | ⏱️ Read time: 10 min read Teach your LLM how to talk through examples

40 151

📌 AI Assistants, Copilots, and Agents in Data & Analytics: What’s the Difference? 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-06-07 | ⏱️ Read time: 8 min read Understanding AI autonomy: assistants, copilots, agents, and their impact on business value

40 151

📌 Scale Is All You Need for Lip-Sync? 🗂 Category: DEEP LEARNING 🕒 Date: 2024-06-07 | ⏱️ Read time: 14 min read Alibaba’s EMO and Microsoft’s VASA-1 are crazy good. Let’s break down how they work.

40 151

📌 Python 3.14 and the End of the GIL 🗂 Category: PROGRAMMING 🕒 Date: 2025-10-18 | ⏱️ Read time: 16 min read Exploring the opportunities and challenges of a GIL-free Python

40 151

📌 Can We Save the AI Economy? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-10-18 | ⏱️ Read time: 23 min read And do we want to?

40 151

📌 How to Build a Generative Search Engine for Your Local Files Using Llama 3 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-06-08 | ⏱️ Read time: 15 min read Use Qdrant, NVidia NIM API, or Llama 3 8B locally for your local GenAI assistant

40 151

📌 What Is a Good Imputation for Missing Values? 🗂 Category: STATISTICS 🕒 Date: 2024-06-08 | ⏱️ Read time: 21 min read My current take on what imputation should be

40 151

📌 Principal Component Analysis Made Easy: A Step-by-Step Tutorial 🗂 Category: DATA SCIENCE 🕒 Date: 2024-06-08 | ⏱️ Read time: 10 min read Implement the PCA algorithm from scratch with Python

40 151

📌 Tiny Time Mixers (TTM): A Powerful Zero-Shot Forecasting Model by IBM 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-06-08 | ⏱️ Read time: 11 min read A new lightweight open-source foundation model