ch
Feedback
Machine Learning

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 40 208 名订阅者,在 技术与应用 类别中位列第 3 344,并在 叙利亚 地区排名第 228

📊 受众指标与增长动态

невідомо 创建以来,项目保持高速增长,吸引了 40 208 名订阅者。

根据 03 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 338,过去 24 小时变化为 9,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 2.04%。内容发布后 24 小时内通常能获得 2.42% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 822 次浏览,首日通常累积 973 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 04 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。

40 208
订阅者
+924 小时
+727
+33830
帖子存档
📌 AI Agents: The Intersection of Tool Calling and Reasoning in Generative AI 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2
📌 AI Agents: The Intersection of Tool Calling and Reasoning in Generative AI 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-10-05 | ⏱️ Read time: 13 min read Unpacking problem solving and tool-driven decision making in AI

📌 How I Turned IPL Stats into a Mesmerizing Bar Chart Race 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-06 | ⏱️ Read time: 8 m
📌 How I Turned IPL Stats into a Mesmerizing Bar Chart Race 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-06 | ⏱️ Read time: 8 min read A step-by-step guide to creating captivating animated visualizations for data storytelling

📌 The Rise of Pallas: Unlocking TPU Potential with Custom Kernels 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-10-06 |
📌 The Rise of Pallas: Unlocking TPU Potential with Custom Kernels 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-10-06 | ⏱️ Read time: 17 min read Accelerating AI/ML Model Training with Custom Operators – Part 3

📌 FormulaFeatures: A Tool to Generate Highly Predictive Features for Interpretable Models 🗂 Category: 🕒 Date: 2024-10-06 |
📌 FormulaFeatures: A Tool to Generate Highly Predictive Features for Interpretable Models 🗂 Category: 🕒 Date: 2024-10-06 | ⏱️ Read time: 41 min read Create more interpretable models by using concise, highly predictive features, automatically engineered based on arithmetic…

📌 Exploring the AI Alignment Problem with GridWorlds 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-10-06 | ⏱️ Read time
📌 Exploring the AI Alignment Problem with GridWorlds 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-10-06 | ⏱️ Read time: 25 min read It’s difficult to build capable AI agents without encountering orthogonal goals

📌 How Did Open Food Facts Fix OCR-Extracted Ingredients Using Open-Source LLMs? 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-
📌 How Did Open Food Facts Fix OCR-Extracted Ingredients Using Open-Source LLMs? 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-06 | ⏱️ Read time: 15 min read Delve into an end-to-end Machine Learning project to improve the quality of the Open Food…

📌 Getting Started with Powerful Data Tables in your Python Web Apps 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-06 | ⏱️ Read
📌 Getting Started with Powerful Data Tables in your Python Web Apps 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-06 | ⏱️ Read time: 6 min read Using AG Grid to build a Finance app in pure Python with Reflex

📌 Top 5 Geospatial Data APIs for Advanced Analysis 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-06 | ⏱️ Read time: 22 min read
📌 Top 5 Geospatial Data APIs for Advanced Analysis 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-06 | ⏱️ Read time: 22 min read Explore Overpass, Geoapify, Distancematrix.ai, Amadeus, and Mapillary for Advanced Mapping and Location Data

📌 Arrays – Data Structures & Algorithms for Data Scientists 🗂 Category: CODING 🕒 Date: 2024-10-07 | ⏱️ Read time: 6 min re
📌 Arrays – Data Structures & Algorithms for Data Scientists 🗂 Category: CODING 🕒 Date: 2024-10-07 | ⏱️ Read time: 6 min read How dynamic and static arrays work under the hood

📌 Discover AWS Lambda Basics to Run Powerful Serverless Functions 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-10-07 |
📌 Discover AWS Lambda Basics to Run Powerful Serverless Functions 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-10-07 | ⏱️ Read time: 12 min read Learn how I navigated setting up AWS Lambda for the first time

📌 AlphaFold 2 Through the Context of BERT 🗂 Category: 🕒 Date: 2024-10-07 | ⏱️ Read time: 9 min read Understanding AI appli
📌 AlphaFold 2 Through the Context of BERT 🗂 Category: 🕒 Date: 2024-10-07 | ⏱️ Read time: 9 min read Understanding AI applications in bio for machine learning engineers

📌 Using Linear Equations + LLM to Solve LinkedIn Queens Game 🗂 Category: 🕒 Date: 2024-10-07 | ⏱️ Read time: 11 min read Pr
📌 Using Linear Equations + LLM to Solve LinkedIn Queens Game 🗂 Category: 🕒 Date: 2024-10-07 | ⏱️ Read time: 11 min read Prompting GPT to form and solve the linear equations using PuLP

📌 Scaling RAG from POC to Production 🗂 Category: CHATGPT 🕒 Date: 2024-10-07 | ⏱️ Read time: 8 min read Common challenges a
📌 Scaling RAG from POC to Production 🗂 Category: CHATGPT 🕒 Date: 2024-10-07 | ⏱️ Read time: 8 min read Common challenges and architectural components to enable scaling

📌 K Nearest Neighbor Regressor, Explained: A Visual Guide with Code Examples 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-07 |
📌 K Nearest Neighbor Regressor, Explained: A Visual Guide with Code Examples 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-07 | ⏱️ Read time: 11 min read Finding the neighbors FAST with KD Trees and Ball Trees

📌 Supercharge Your LLM Apps using DSPy and Langfuse 🗂 Category: NATURAL LANGUAGE PROCESSING 🕒 Date: 2024-10-07 | ⏱️ Read t
📌 Supercharge Your LLM Apps using DSPy and Langfuse 🗂 Category: NATURAL LANGUAGE PROCESSING 🕒 Date: 2024-10-07 | ⏱️ Read time: 14 min read Build Production Grade LLM Apps with Ease

📌 Implementing Sequential Algorithms on TPU 🗂 Category: 🕒 Date: 2024-10-07 | ⏱️ Read time: 13 min read Accelerating AI/ML
📌 Implementing Sequential Algorithms on TPU 🗂 Category: 🕒 Date: 2024-10-07 | ⏱️ Read time: 13 min read Accelerating AI/ML Model Training with Custom Operators – Part 3.A

📌 How to Talk About Data and Analysis Simply 🗂 Category: 🕒 Date: 2024-10-08 | ⏱️ Read time: 21 min read So that it is unde
📌 How to Talk About Data and Analysis Simply 🗂 Category: 🕒 Date: 2024-10-08 | ⏱️ Read time: 21 min read So that it is understandable and engaging to (almost) everyone

📌 Pandora’s Cloud Migration: Conquer the 7 “Bringers of Evil” 🗂 Category: 🕒 Date: 2024-10-08 | ⏱️ Read time: 20 min read A
📌 Pandora’s Cloud Migration: Conquer the 7 “Bringers of Evil” 🗂 Category: 🕒 Date: 2024-10-08 | ⏱️ Read time: 20 min read A guide to conquering cloud migration challenges

📌 Adding Gradient Backgrounds to Plotly Charts 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-08 | ⏱️ Read time: 5 min read Usin
📌 Adding Gradient Backgrounds to Plotly Charts 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-08 | ⏱️ Read time: 5 min read Using Plotly rectangle shapes to improve data visualisation

📌 Precisely Compare Geographical Regions with GeoPandas 🗂 Category: 🕒 Date: 2024-10-08 | ⏱️ Read time: 9 min read Filling
📌 Precisely Compare Geographical Regions with GeoPandas 🗂 Category: 🕒 Date: 2024-10-08 | ⏱️ Read time: 9 min read Filling maps with area measurements