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 40 149 名订阅者,在 技术与应用 类别中位列第 3 375,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 40 149 名订阅者。
根据 28 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 378,过去 24 小时变化为 7,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 2.09%。内容发布后 24 小时内通常能获得 1.91% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 841 次浏览,首日通常累积 766 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 29 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。
40 149
订阅者
+724 小时
+1147 天
+37830 天
帖子存档
40 150
📌 AI Training Simplified: The Essential Mathematics Explained
🗂 Category: DATA SCIENCE
🕒 Date: 2024-07-06 | ⏱️ Read time: 4 min read
An Illustrated Overview of Mathematical Logic Used in AI Training
40 150
📌 Understanding and Implementing Medprompt
🗂 Category: CHATGPT
🕒 Date: 2024-07-06 | ⏱️ Read time: 16 min read
Digging into the details behind the prompting framework
40 150
📌 Optimum Assignment and the Hungarian Algorithm
🗂 Category: DATA SCIENCE
🕒 Date: 2024-07-07 | ⏱️ Read time: 13 min read
This article provides a step by step example of how the Hungarian algorithm solves the…
40 150
🤖🧠 Grok AI Chatbot (2025): Elon Musk’s Bold Answer to Real-Time, Intelligent Conversation
🗓️ 12 Oct 2025
📚 AI News & Trends
The year 2025 marks a new era in the evolution of conversational AI and at the center of this transformation stands Grok AI, the innovative chatbot developed by Elon Musk’s company xAI. Grok isn’t just another virtual assistant; it’s a real-time intelligent system that combines deep reasoning with a unique, witty personality. What truly sets ...
#GrokAI #xAI #ConversationalAI #ElonMusk #RealTimeAI #IntelligentChatbot
40 150
📌 Neural Network (MLP) for Time Series Forecasting in Practice
🗂 Category: DATA SCIENCE
🕒 Date: 2024-07-08 | ⏱️ Read time: 18 min read
A Practical Example for Feature Engineering and Constructing an MLP Model
40 150
📌 AI Is Eating Your Algorithms
🗂 Category: CHATGPT
🕒 Date: 2024-07-08 | ⏱️ Read time: 10 min read
How simple prompt engineering can replace custom software
40 150
📌 How Many Cars Are in This Aerial Imagery? Let’s Count Them with YOLOv8 from Scratch!
🗂 Category: DATA SCIENCE
🕒 Date: 2024-07-08 | ⏱️ Read time: 14 min read
A Step-by-Step Guide to Deploy YOLOv8 for Object Detection and Counting on Your Customized Database…
40 150
📌 Creative Canvas: Using AI to Paint, Edit, and Stylize Images
🗂 Category:
🕒 Date: 2024-07-08 | ⏱️ Read time: 22 min read
I explored commercial and open-source photo editing systems for the creative use of AI image…
40 150
🤖🧠 Artificial Intelligence: A Modern Approach — The Ultimate Number 1 Guide to Learning AI by Stuart Russell and Peter Norvig
🗓️ 12 Oct 2025
📚 AI News & Trends
When it comes to learning artificial intelligence (AI), few resources hold as much authority as “Artificial Intelligence: A Modern Approach” by Stuart Russell and Peter Norvig. Often regarded as the “Bible of AI”, this textbook has become the most widely used academic reference in the field adopted by over 1,500 universities and institutions worldwide. Published ...
#ArtificialIntelligence #AIModernApproach #StuartRussell #PeterNorvig #AIBible #AIEducation
40 150
📌 Is LLM Performance Predetermined by Their Genetic Code?
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-07-08 | ⏱️ Read time: 9 min read
Exploring phylogenetic algorithms to predict the future of large language models
40 150
📌 NLP: Text Summarization and Keyword Extraction on Property Rental Listings – Part 1
🗂 Category: DATA SCIENCE
🕒 Date: 2024-07-08 | ⏱️ Read time: 13 min read
A practical implementation of NLP techniques such as text summarization, NER, topic modeling, and text…
40 150
📌 TensorFlow Transform: Ensuring Seamless Data Preparation in Production
🗂 Category: DATA ENGINEERING
🕒 Date: 2024-07-08 | ⏱️ Read time: 10 min read
Leveraging TensorFlow Transform for scaling data pipelines for production environments
40 150
📌 Implementing Neural Networks in TensorFlow (and PyTorch)
🗂 Category: DEEP LEARNING
🕒 Date: 2024-07-08 | ⏱️ Read time: 6 min read
Step-by-step code guide on building a Neural Network
40 150
📌 Doping: A Technique to Test Outlier Detectors
🗂 Category:
🕒 Date: 2024-07-09 | ⏱️ Read time: 18 min read
Using well-crafted synthetic data to compare and evaluate outlier detectors
40 150
📌 Tracking in Practice: Code, Data and ML Model
🗂 Category: MACHINE LEARNING
🕒 Date: 2024-07-09 | ⏱️ Read time: 13 min read
A guide to tracking in MLOps
40 150
📌 Spicing up Ice Hockey with AI: Player Tracking with Computer Vision
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-07-09 | ⏱️ Read time: 35 min read
Using PyTorch, computer vision techniques, and a CNN, I worked on a model that tracks…
40 150
📌 Perception-Inspired Graph Convolution for Music Understanding Tasks
🗂 Category:
🕒 Date: 2024-07-09 | ⏱️ Read time: 12 min read
This article discusses MusGConv, a perception-inspired graph convolution block for symbolic musical applications.
40 150
Ever wondered why some wines taste like liquid silk while others burst with crisp, electric freshness? Unlock the secrets of terroir, barrel, and grape—without the snobbery. Simply Wine brings you honest reviews, hidden gems, and stories that make every sip unforgettable. Want to truly taste what’s in your glass? Explore with us and savor wine like never before.
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40 150
📌 Deep Dive into LSTMs & xLSTMs by Hand
🗂 Category: DEEP LEARNING
🕒 Date: 2024-07-09 | ⏱️ Read time: 13 min read
Explore the wisdom of LSTM leading into xLSTMs - a probable competition to the present-day LLMs
40 150
📌 Conversational Analysis Is the Future for Enterprise Data Science
🗂 Category: DATA SCIENCE
🕒 Date: 2024-07-09 | ⏱️ Read time: 9 min read
LLMs won’t replace data scientists, but they will change how we collaborate with decision makers
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