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228 技术与应用3 344...

📈 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 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 40 208 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 天

+33830 天

822

帖子浏览量

~ 97324 小时

~ 1 32148 小时

2.04%

参与率

~ 3

每日帖子数

Ads index

beta

帖子存档

40 222

📌 How to Choose the Best ML Deployment Strategy: Cloud vs. Edge 🗂 Category: 🕒 Date: 2024-10-14 | ⏱️ Read time: 17 min read The choice between cloud and edge deployment could make or break your project

40 222

📌 Evaluating synthetic data 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-14 | ⏱️ Read time: 9 min read Assessing plausibility and usefulness of data we generated from real data

40 222

📌 AI Feels Easier Than Ever, But Is It Really? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-10-15 | ⏱️ Read time: 9 min read The 4 big challenges of building AI products

40 222

📌 I Built An AI Human-Level Game Player 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-10-15 | ⏱️ Read time: 13 min read Old-school game trees can be incredibly effective.

40 222

📌 Dataflow architecture 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-10-15 | ⏱️ Read time: 23 min read on derived data views and eventual consistency

40 222

📌 I Fine-Tuned the Tiny Llama 3.2 1B to Replace GPT-4o 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-15 | ⏱️ Read time: 8 min read Is the fine-tuning effort worth more than few-shot prompting?

40 222

📌 Continual Learning: A Primer 🗂 Category: DEEP LEARNING 🕒 Date: 2024-10-15 | ⏱️ Read time: 8 min read Plus paper recommendations

40 222

📌 Normalized Discounted Cumulative Gain (NDCG) – The Ultimate Ranking Metric 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-15 | ⏱️ Read time: 10 min read NDCG – The Rank-Aware Metric for Evaluating Recommendation Systems

40 222

📌 Will Your Vote Decide the Next President? 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-15 | ⏱️ Read time: 22 min read Simulating the probability that your singular vote swings the election in November

40 222

📌 Beyond Naive RAG: Advanced Techniques for Building Smarter and Reliable AI Systems 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-10-16 | ⏱️ Read time: 32 min read A deep dive into advanced indexing, pre-retrieval, retrieval, and post-retrieval techniques to enhance RAG performance

40 222

📌 Marketing Mix Modeling (MMM): How to Avoid Biased Channel Estimates 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-16 | ⏱️ Read time: 16 min read Learn which variables you should and should not take into account in your model.

40 222

📌 The Science Behind AI’s First Nobel Prize 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-16 | ⏱️ Read time: 13 min read How Physics and Machine Learning Joined Forces to Win Physics Nobel 2024

40 222

📌 Exploring DRESS Kit V2 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-16 | ⏱️ Read time: 13 min read Exploring new features and notable changes in the latest version of the DRESS Kit

40 222

📌 A Novel Approach to Detect Coordinated Attacks Using Clustering 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-16 | ⏱️ Read time: 18 min read Unveiling hidden patterns: grouping malicious behavior

40 222

📌 Visualization of Data with Pie Charts in Matplotlib 🗂 Category: 🕒 Date: 2024-10-16 | ⏱️ Read time: 5 min read Examples of how to create different types of pie charts using Matplotlib to visualize the…

40 222

📌 Temporal-Difference Learning: Combining Dynamic Programming and Monte Carlo Methods for Reinforcement Learning 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-17 | ⏱️ Read time: 17 min read Milestones of RL: Q-Learning and Double Q-Learning

40 222

📌 Create Your Own Prompt Enhancer from Scratch 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-10-17 | ⏱️ Read time: 11 min read How to emulate OpenAI’s system prompt generator functionality

40 222

📌 Fine-Tuning BERT for Text Classification 🗂 Category: DEEP LEARNING 🕒 Date: 2024-10-17 | ⏱️ Read time: 6 min read A hackable example with Python code

40 222

📌 All You Need to Know to Build Radial Charts in Tableau 🗂 Category: DATA SCIENCE 🕒 Date: 2024-10-17 | ⏱️ Read time: 7 min read You will never forget it after this!

40 222

📌 A Critical Look at AI Image Generation 🗂 Category: ART 🕒 Date: 2024-10-17 | ⏱️ Read time: 12 min read What does image generative AI really tell us about our world?