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 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
帖子存档
40 221
📌 Automatic Differentiation (AutoDiff): A Brief Intro with Examples
🗂 Category: DEEP LEARNING
🕒 Date: 2024-10-11 | ⏱️ Read time: 11 min read
An introduction to the mechanics of AutoDiff, exploring its mathematical principles, implementation strategies, and applications
40 221
📌 Topic Alignment for NLP Recommender Systems
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-10-11 | ⏱️ Read time: 18 min read
Leveraging topic modeling to align user queries with document themes, enhancing the relevance and contextual…
40 221
📌 A Mixed-Methods Approach to Offline Evaluation of News Recommender Systems
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-10-11 | ⏱️ Read time: 8 min read
Combining reader feedback from surveys with behavioral click data to optimize content personalization.
40 221
📌 Understanding Automatic Differentiation in JAX: A Deep Dive
🗂 Category: DEEP LEARNING
🕒 Date: 2024-10-11 | ⏱️ Read time: 12 min read
Unleashing the Gradient: How JAX Makes Automatic Differentiation Feel Like Magic
40 221
📌 Common Misconceptions About Data Science
🗂 Category: CAREER ADVICE
🕒 Date: 2024-10-11 | ⏱️ Read time: 7 min read
Data science advice that you should question
40 221
📌 Bursting the AI Hype Bubble Once and for All
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-10-12 | ⏱️ Read time: 11 min read
Misinformation and poor research: a case study
40 221
📌 Gaussian Naive Bayes, Explained: A Visual Guide with Code Examples for Beginners
🗂 Category: DATA SCIENCE
🕒 Date: 2024-10-12 | ⏱️ Read time: 8 min read
Bell-shaped assumptions for better predictions
40 221
📌 Improve Your RAG Context Recall by 95% with an Adapted Embedding Model.
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2024-10-12 | ⏱️ Read time: 11 min read
Step by Step Model Adaptation Code and Results Attached.
40 221
📌 Why the 2024 Nobel Prize in (AI for) Chemistry Matters So Much
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-10-12 | ⏱️ Read time: 6 min read
To Demis Hassabis and John Jumper, from DeepMind, and to David Baker, leader of the…
40 221
📌 Upgrading to Prefect Push Workers on AWS ECS
🗂 Category: DATA ENGINEERING
🕒 Date: 2024-10-12 | ⏱️ Read time: 6 min read
Upgrade from Prefect 2.0 to 3.0 and use the new Push Work Pools that greatly…
40 221
📌 Linear Discriminant Analysis (LDA)
🗂 Category: MACHINE LEARNING
🕒 Date: 2024-10-12 | ⏱️ Read time: 13 min read
Discover how LDA helps identify critical data features
40 221
📌 Top 5 Principles for Building User-Friendly Data Tables
🗂 Category: DATA ENGINEERING
🕒 Date: 2024-10-13 | ⏱️ Read time: 9 min read
Designing intuitive and reliable tables that your data team will love
40 221
📌 Recruiting vs. Interviewing for Data Roles in Diverse Markets
🗂 Category: CAREER ADVICE
🕒 Date: 2024-10-13 | ⏱️ Read time: 12 min read
Factors of success in recruiting and interviewing after applying for 150+ positions and reviewing 500+…
40 221
📌 How to Perform A/B Testing with Hypothesis Testing in Python: A Comprehensive Guide
🗂 Category: DATA SCIENCE
🕒 Date: 2024-10-13 | ⏱️ Read time: 11 min read
A Step-by-Step Guide to Making Data-Driven Decisions with Practical Python Examples
40 221
📌 Bringing Structure to Your Data
🗂 Category:
🕒 Date: 2024-10-14 | ⏱️ Read time: 13 min read
Testing assumptions with path models
40 221
📌 lintsampler: a new way to quickly get random samples from any distribution
🗂 Category: PROBABILITY
🕒 Date: 2024-10-14 | ⏱️ Read time: 5 min read
lintsampler is a pure Python package that can easily and efficiently generate random samples from…
40 221
📌 Product-Oriented ML: A Guide for Data Scientists
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-10-14 | ⏱️ Read time: 30 min read
How to build ML products users love
40 221
📌 How to Set Bid Guardrails in PPC Marketing
🗂 Category: DATA SCIENCE
🕒 Date: 2024-10-14 | ⏱️ Read time: 14 min read
Without controls, bidding algorithms can be quite volatile. Learn how to protect performance through adding…
40 221
📌 PyTorch Optimizers Aren’t Fast Enough. Try These Instead
🗂 Category: DATA SCIENCE
🕒 Date: 2024-10-14 | ⏱️ Read time: 12 min read
These 4 advanced optimizers will open your mind.
40 221
📌 Florence-2: Advancing Multiple Vision Tasks with a Single VLM Model
🗂 Category:
🕒 Date: 2024-10-14 | ⏱️ Read time: 8 min read
A Guided Exploration of Florence-2’s Zero-Shot Capabilities: Captioning, Object Detection, Segmentation and OCR.
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