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 40 150 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
帖子存档
40 148
📌 Roadmap to Becoming a Data Scientist, Part 4: Advanced Machine Learning
🗂 Category: DATA SCIENCE
🕒 Date: 2025-02-14 | ⏱️ Read time: 15 min read
Introduction Data science is undoubtedly one of the most fascinating fields today. Following significant breakthroughs in…
40 148
📌 On-Device Machine Learning in Spatial Computing
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-02-17 | ⏱️ Read time: 18 min read
The landscape of computing is undergoing a profound transformation with the emergence of spatial computing…
40 148
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40 148
📌 Deep Dive into Anthropic’s Sparse Autoencoders by Hand
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2024-05-31 | ⏱️ Read time: 12 min read
Explore the concepts behind the interpretability quest for LLMs
40 148
📌 A Deep Dive into In-Context Learning
🗂 Category: NATURAL LANGUAGE PROCESSING
🕒 Date: 2024-05-31 | ⏱️ Read time: 11 min read
Stepping out of the “comfort zone” – part 2/3 of a deep-dive into domain adaptation…
40 148
📌 YOLO – Intuitively and Exhaustively Explained
🗂 Category: MACHINE LEARNING
🕒 Date: 2024-05-31 | ⏱️ Read time: 31 min read
The genesis of the most widely used object detection models.
40 148
📌 AI Use Cases are Fundamentally Different
🗂 Category: ROBOTICS
🕒 Date: 2024-05-31 | ⏱️ Read time: 9 min read
How to find unique use cases for AI and places where moderate AI performance is…
40 148
📌 Why You Don’t Need JS to Make 3D plots
🗂 Category: DATA SCIENCE
🕒 Date: 2024-06-01 | ⏱️ Read time: 6 min read
Visualizing crime geodata in python
40 148
📌 Performance Insights from Sigma Rule Detections in Spark Streaming
🗂 Category: CYBERSECURITY
🕒 Date: 2024-06-01 | ⏱️ Read time: 13 min read
Utilizing Sigma rules for anomaly detection in cybersecurity logs: A study on performance optimization
40 148
📌 PRISM-Rules in Python
🗂 Category: DATA SCIENCE
🕒 Date: 2024-06-02 | ⏱️ Read time: 14 min read
A simple python rules-induction system
40 148
📌 How I Use ChatGPT As A Data Scientist
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-06-02 | ⏱️ Read time: 8 min read
How ChatGPT improved my productivity as a data scientist
40 148
📌 Comparing Country Sizes with GeoPandas
🗂 Category:
🕒 Date: 2024-06-02 | ⏱️ Read time: 14 min read
How to project, shift, and rotate geospatial data
40 148
📌 Measuring The Intrinsic Causal Influence Of Your Marketing Campaigns
🗂 Category: DATA SCIENCE
🕒 Date: 2024-06-02 | ⏱️ Read time: 11 min read
Causal AI, exploring the integration of causal reasoning into machine learning
40 148
📌 Linear Attention Is All You Need
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2024-06-02 | ⏱️ Read time: 10 min read
Self-attention at a fraction of the cost?
40 148
📌 ML Engineering 101: A Thorough Explanation of The Error “DataLoader worker (pid(s) xxx) exited…
🗂 Category: DATA SCIENCE
🕒 Date: 2024-06-03 | ⏱️ Read time: 6 min read
A deep dive into PyTorch DataLoader with Multiprocessing
40 148
📌 Optimizing Memory Consumption for Data Analytics Using Python – From 400 to 0.1
🗂 Category: DATA SCIENCE
🕒 Date: 2024-06-03 | ⏱️ Read time: 9 min read
Reducing the memory consumption of your code means reducing hardware requirements
40 148
📌 Bit-LoRA as an application of BitNet and 1.58 bit neural network technologies
🗂 Category:
🕒 Date: 2024-06-03 | ⏱️ Read time: 15 min read
Abstract: applying ~1bit transformer technology to LoRA adapters allows us to reach comparable performance with…
40 148
📌 The Trap of Sprints: Don’t Be Like Scarlett O’Hara. Think Today!
🗂 Category: AGILE
🕒 Date: 2024-06-03 | ⏱️ Read time: 11 min read
Why data scientists should prioritize communication and flexibility in agile projects
40 148
📌 A Deep Dive into Fine-Tuning
🗂 Category: NATURAL LANGUAGE PROCESSING
🕒 Date: 2024-06-03 | ⏱️ Read time: 30 min read
Stepping out of the “comfort zone” – part 3/3 of a deep-dive into domain adaptation…
40 148
📌 The Meaning of Explainability for AI
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-06-04 | ⏱️ Read time: 10 min read
Do we still care about how our machine learning does what it does?
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