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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 40 106 подписчиков, занимая 3 384 место в категории Технологии и приложения и 231 место в регионе Сирия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 40 106 подписчиков.
Согласно последним данным от 24 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 401, а за последние 24 часа — 38, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 1.96%. В первые 24 часа после публикации контент обычно набирает 1.16% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 788 просмотров. В течение первых суток публикация набирает 465 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 2.
- 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 25 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.
40 106
Подписчики
+3824 часа
+637 дней
+40130 день
Архив постов
40 114
📌 Prompt Engineering vs RAG for Editing Resumes
🗂 Category: LLM APPLICATIONS
🕒 Date: 2026-01-04 | ⏱️ Read time: 12 min read
Running a code-free comparison in Azure
#DataScience #AI #Python
40 114
📌 How to Keep MCPs Useful in Agentic Pipelines
🗂 Category: AGENTIC AI
🕒 Date: 2026-01-03 | ⏱️ Read time: 10 min read
Check the tools your LLM uses before replacing it with just a more powerful model
#DataScience #AI #Python
40 114
📌 Optimizing Data Transfer in AI/ML Workloads
🗂 Category: DEEP LEARNING
🕒 Date: 2026-01-03 | ⏱️ Read time: 16 min read
A deep dive on data transfer bottlenecks, their identification, and their resolution with the help…
#DataScience #AI #Python
40 114
200$ to 20k$ SOL Challenge!
As promised, i will do another challenge for those who missed the previous one!
Last one we completed in 6 days, let’s do this one even quicker!
Join my free group Before closing 👇
https://t.me/+DAKLP7eUy9Y3ZjY0
#ad InsideAds
40 114
Repost from Machine Learning with Python
All assignments for the #Stanford The Modern Software Developer course are now available online.
This is the first full-fledged university course that covers how code-generative #LLMs are changing every stage of the development lifecycle. The assignments are designed to take you from a beginner to a confident expert in using AI to boost productivity in development.
Enjoy your studies! ✌️
https://github.com/mihail911/modern-software-dev-assignments
https://t.me/CodeProgrammer
40 114
📌 The Real Challenge in Data Storytelling: Getting Buy-In for Simplicity
🗂 Category: DATA SCIENCE
🕒 Date: 2026-01-02 | ⏱️ Read time: 7 min read
What happens when your clear dashboard meets stakeholders who want everything on one screen
#DataScience #AI #Python
40 114
📌 Off-Beat Careers That Are the Future Of Data
🗂 Category: DATA SCIENCE
🕒 Date: 2026-01-02 | ⏱️ Read time: 8 min read
The unconventional career paths you need to explore
#DataScience #AI #Python
40 114
📌 Drift Detection in Robust Machine Learning Systems
🗂 Category: MACHINE LEARNING
🕒 Date: 2026-01-02 | ⏱️ Read time: 18 min read
A prerequisite for long-term success of machine learning systems
#DataScience #AI #Python
40 114
200$ to 20k$ SOL Challenge!
As promised, i will do another challenge for those who missed the previous one!
Last one we completed in 6 days, let’s do this one even quicker!
Join my free group Before closing 👇
https://t.me/+DAKLP7eUy9Y3ZjY0
#ad InsideAds
40 114
📌 Deep Reinforcement Learning: The Actor-Critic Method
🗂 Category: REINFORCEMENT LEARNING
🕒 Date: 2026-01-01 | ⏱️ Read time: 19 min read
Robot friends collaborate to learn to fly a drone
#DataScience #AI #Python
40 114
Repost from Machine Learning with Python
Harvard has made its textbook on ML systems publicly available. It's extremely practical: not just about how to train models, but how to build production systems around them - what really matters.
The topics there are really top-notch:
> Building autograd, optimizers, attention, and mini-PyTorch from scratch to understand how the framework is structured internally. (This is really awesome)
> Basic things about DL: batches, computational accuracy, model architectures, and training
> Optimizing ML performance, hardware acceleration, benchmarking, and efficiency
So this isn't just an introductory course on ML, but a complete cycle from start to practical application. You can already read the book and view the code for free. For 2025, this is one of the strongest textbooks to have been released, so it's best not to miss out.
The repository is here, with a link to the book inside 👏
👉 @codeprogrammer
40 114
📌 EDA in Public (Part 3): RFM Analysis for Customer Segmentation in Pandas
🗂 Category: DATA SCIENCE
🕒 Date: 2026-01-01 | ⏱️ Read time: 13 min read
How to build, score, and interpret RFM segments step by step
#DataScience #AI #Python
40 114
📌 The Machine Learning “Advent Calendar” Bonus 2: Gradient Descent Variants in Excel
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-31 | ⏱️ Read time: 8 min read
Gradient Descent, Momentum, RMSProp, and Adam all aim for the same minimum. They do not…
#DataScience #AI #Python
40 114
📌 Chunk Size as an Experimental Variable in RAG Systems
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-12-31 | ⏱️ Read time: 12 min read
Understanding retrieval in RAG systems by experimenting with different chunk sizes
#DataScience #AI #Python
40 114
📌 What Advent of Code Has Taught Me About Data Science
🗂 Category: PROGRAMMING
🕒 Date: 2025-12-31 | ⏱️ Read time: 10 min read
Five key learnings that I discovered during a programming challenge and how they apply to…
#DataScience #AI #Python
40 114
📌 Production-Ready LLMs Made Simple with the NeMo Agent Toolkit
🗂 Category: AGENTIC AI
🕒 Date: 2025-12-31 | ⏱️ Read time: 23 min read
From simple chat to multi-agent reasoning and real-time REST APIs
#DataScience #AI #Python
40 114
“I spent hours lost in endless Telegram groups—until I discovered this hidden search engine.” Argo🔍Search lets you find the best groups, channels, music, and news in seconds. No more wasting time scrolling!
Discover what others haven’t yet: Try it now and unlock Telegram like never before.
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