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Machine Learning
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Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho
Больше📈 Аналитический обзор Telegram-канала Machine Learning
Канал Machine Learning (@machinelearning9) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 40 151 подписчиков, занимая 3 380 место в категории Технологии и приложения и 228 место в регионе Сирия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 40 151 подписчиков.
Согласно последним данным от 29 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 380, а за последние 24 часа — 3, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 2.08%. В первые 24 часа после публикации контент обычно набирает 1.91% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 837 просмотров. В течение первых суток публикация набирает 766 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 3.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как distance, insidead, gpu, learning, degree.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“Real Machine Learning — simple, practical, and built on experience.
Learn step by step with clear explanations and working code.
Admin: @HusseinSheikho || @Hussein_Sheikho”
Благодаря высокой частоте обновлений (последние данные получены 30 июня, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Технологии и приложения.
40 151
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+324 часа
+1157 дней
+38030 день
Архив постов
40 150
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40 150
📌 Towards Generalization on Graphs: From Invariance to Causality
🗂 Category: DATA SCIENCE
🕒 Date: 2024-07-18 | ⏱️ Read time: 19 min read
This blog post shares recent papers on out-of-distribution generalization on graph-structured data
40 150
📌 A Python Engineer’s Introduction to 3D Gaussian Splatting (Part 3)
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-07-18 | ⏱️ Read time: 9 min read
Part 3 of our Gaussian Splatting tutorial, showing how to render splats onto a 2D…
40 150
📌 YOLO inference with Docker via API
🗂 Category: DEEP LEARNING
🕒 Date: 2024-07-19 | ⏱️ Read time: 16 min read
Learn how to orchestrate object detection inference via a REST API with Docker
40 150
📌 Product Quasi-Experimentation: Statistical Techniques When Standard A/B Testing Is Not Possible
🗂 Category: DATA SCIENCE
🕒 Date: 2024-07-19 | ⏱️ Read time: 6 min read
A guide to the most popular techniques when randomized A/B testing is not possible
40 150
📌 Constrained Sentence Generation Using Gibbs Sampling and BERT
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2024-07-19 | ⏱️ Read time: 11 min read
A fast and effective approach to generating fluent sentences from given keywords using public pre-trained…
40 150
📌 Evaluating ChatGPT’s Data Analysis Improvements: Interactive Tables and Charts
🗂 Category: CHATGPT
🕒 Date: 2024-07-19 | ⏱️ Read time: 11 min read
Is ChatGPT becoming a BI tool?
40 150
📌 Streamlining Object Detection with Metaflow, AWS, and Weights & Biases
🗂 Category:
🕒 Date: 2024-07-19 | ⏱️ Read time: 18 min read
How to create a production-grade pipeline for object detection
40 150
📌 Battling Open Book Exams with Open Source LLMs
🗂 Category: DATA SCIENCE
🕒 Date: 2024-07-19 | ⏱️ Read time: 10 min read
In the age where everyone uses ChatGPT for work and school, I am taking advantage…
40 150
📌 Understanding Positional Embeddings in Transformers: From Absolute to Rotary
🗂 Category: DEEP LEARNING
🕒 Date: 2024-07-20 | ⏱️ Read time: 19 min read
A deep dive into absolute, relative, and rotary positional embeddings with code examples
40 150
📌 Three Mind-Blowing Ideas in Physics: The Stationary Action Principle, Lorentz Transformations, and…
🗂 Category: DATA SCIENCE
🕒 Date: 2024-07-23 | ⏱️ Read time: 31 min read
How mathematical innovations yield increasingly more accurate models of the physical world
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📌 Counterfactuals in Language AI
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2024-07-23 | ⏱️ Read time: 34 min read
with open source language models and LLMs
40 150
📌 Line By Line, Let’s Reproduce GPT-2: Section 1
🗂 Category:
🕒 Date: 2024-07-23 | ⏱️ Read time: 26 min read
This blog post will go line-by-line through the code in Section 1 of Andrej Karpathy’s…
40 150
📌 I Used to Hate Overfitting, But Now I’m Grokking It
🗂 Category: DATA SCIENCE
🕒 Date: 2024-07-23 | ⏱️ Read time: 9 min read
The surprising generalisation beyond overfitting
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📌 Summer Olympic Games Through the Lens of Data
🗂 Category: DATA SCIENCE
🕒 Date: 2024-07-23 | ⏱️ Read time: 13 min read
Using Python and Wikipedia to draw geographical and network maps of the medal-winning countries.
40 150
📌 From Ephemeral to Persistence with LangChain: Building Long-Term Memory in Chatbots
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-07-23 | ⏱️ Read time: 8 min read
A detailed walkthrough on transforming simple chatbots into sophisticated AI assistants with long-term memory and…
40 150
📌 Evolution of Data Science: New Age Skills for the Modern End-to-End Data Scientist
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-07-23 | ⏱️ Read time: 27 min read
From Python scripting to data engineering, MLOps, and GenAI
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📌 Organizations’ Machine Learning Investment Is (or Should Be) Incremental
🗂 Category: DATA SCIENCE
🕒 Date: 2024-07-23 | ⏱️ Read time: 8 min read
Embedding ML systems into production is still a hard thing to do (for most companies)
40 150
📌 Monocular Depth Estimation with Depth Anything V2
🗂 Category: DEEP LEARNING
🕒 Date: 2024-07-24 | ⏱️ Read time: 11 min read
How do neural networks learn to estimate depth from 2D images?
40 150
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