ru
Feedback
Machine Learning

Machine Learning

Открыть в Telegram

Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho

Больше
Machine Learning with PythonСеть:Machine Learning with PythonСирия228Технологии и приложения3 352

📈 Аналитический обзор Telegram-канала Machine Learning

Канал Machine Learning (@machinelearning9) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 40 205 подписчиков, занимая 3 352 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 40 205 подписчиков.

Согласно последним данным от 02 июля, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 343, а за последние 24 часа — 10, при этом общий охват остаётся высоким.

  • Статус верификации: Не верифицирован
  • Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 1.99%. В первые 24 часа после публикации контент обычно набирает 2.28% реакций от общего числа подписчиков.
  • Охват публикаций: В среднем каждый пост получает 800 просмотров. В течение первых суток публикация набирает 915 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 03 июля, 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.

40 205
Подписчики
+1024 часа
+837 дней
+34330 день
Архив постов
Machine Learning
Machine Learningverified-telegram-icon
40 210
🌍 Work Abroad for Skilled Construction Workers! Salary: $450–700 per month ✅ Free accommodation ✅ Free meals ✅ Official 1-ye
🌍 Work Abroad for Skilled Construction Workers! Salary: $450–700 per month ✅ Free accommodation ✅ Free meals ✅ Official 1-year work contract 📌 Open positions: • Tilers • Painters / Plasterers • Bricklayers • Facade Workers • Plumbers • Electricians 💡 Experience required! 📲 Apply now #ad InsideAds

Machine Learning
Machine Learningverified-telegram-icon
40 210
“I deposited $1,000 and saw my trading capital DOUBLE before I even placed my first trade.” Want to know how this bonus trick
“I deposited $1,000 and saw my trading capital DOUBLE before I even placed my first trade.” Want to know how this bonus trick works and who else is secretly using it? Watch the real results from Elite Gold Trading 👉 right here — hurry, this offer won’t wait. #ad InsideAds

Machine Learning
Machine Learningverified-telegram-icon
40 210
I thought I’d read every secret manga out there… but last night I stumbled onto a title so wild it blew my mind. I can’t beli
I thought I’d read every secret manga out there… but last night I stumbled onto a title so wild it blew my mind. I can’t believe no one is talking about it. Want to know the name? Find it right here before it disappears. #ad InsideAds

Machine Learning
Machine Learningverified-telegram-icon
40 210
📌 Uncertainty in Markov Decisions Processes: a Robust Linear Programming approach 🗂 Category: MATH 🕒 Date: 2024-09-18 | ⏱️
📌 Uncertainty in Markov Decisions Processes: a Robust Linear Programming approach 🗂 Category: MATH 🕒 Date: 2024-09-18 | ⏱️ Read time: 8 min read Theoretical derivation of the Robust Counterpart of Markov Decision Processes (MDPs) as a Linear Program…

Machine Learning
Machine Learningverified-telegram-icon
40 210
📌 Principal Component Analysis – Hands-On Tutorial 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-18 | ⏱️ Read time: 13 min read
📌 Principal Component Analysis – Hands-On Tutorial 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-18 | ⏱️ Read time: 13 min read Dimensionality reduction through Principal Component Analysis (PCA).

Machine Learning
Machine Learningverified-telegram-icon
40 210
“I never thought a $1,000 account could grow like this—until I saw how the Elite Gold Trading community does it every day!” M
“I never thought a $1,000 account could grow like this—until I saw how the Elite Gold Trading community does it every day!” Most traders lose by chasing quick wins. The real secret? Consistent, low-risk profits. Ready to see proof? Check this right now — don’t let others get ahead of you! #ad InsideAds

Machine Learning
Machine Learningverified-telegram-icon
40 210
📌 A Visual Exploration of Semantic Text Chunking 🗂 Category: NATURAL LANGUAGE PROCESSING 🕒 Date: 2024-09-19 | ⏱️ Read time
📌 A Visual Exploration of Semantic Text Chunking 🗂 Category: NATURAL LANGUAGE PROCESSING 🕒 Date: 2024-09-19 | ⏱️ Read time: 22 min read Use embeddings and visualization tools to split text into meaningful chunks

Machine Learning
Machine Learningverified-telegram-icon
40 210
📌 Emerging Tech Is Nothing Without Methodology 🗂 Category: ANALYTICS 🕒 Date: 2024-09-19 | ⏱️ Read time: 6 min read Or: a H
📌 Emerging Tech Is Nothing Without Methodology 🗂 Category: ANALYTICS 🕒 Date: 2024-09-19 | ⏱️ Read time: 6 min read Or: a Hundred Ways to Solve a Complex Problem

Machine Learning
Machine Learningverified-telegram-icon
40 210
📌 A Closer Look at Scipy’s Stats module – Part 1 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-19 | ⏱️ Read time: 7 min read Le
📌 A Closer Look at Scipy’s Stats module – Part 1 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-19 | ⏱️ Read time: 7 min read Let’s learn the main methods from scipy.stats module in Python.

Machine Learning
Machine Learningverified-telegram-icon
40 210
📌 A Closer Look at Scipy’s Stats Module – Part 2 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-19 | ⏱️ Read time: 6 min read Le
📌 A Closer Look at Scipy’s Stats Module – Part 2 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-19 | ⏱️ Read time: 6 min read Let’s learn the main methods from scipy.stats module in Python.

Machine Learning
Machine Learningverified-telegram-icon
40 210
📌 How to Build Your Own Roadmap for a Successful Data Science Career 🗂 Category: CAREER ADVICE 🕒 Date: 2024-09-19 | ⏱️ Rea
📌 How to Build Your Own Roadmap for a Successful Data Science Career 🗂 Category: CAREER ADVICE 🕒 Date: 2024-09-19 | ⏱️ Read time: 4 min read Our weekly selection of must-read Editors’ Picks and original features

Machine Learning
Machine Learningverified-telegram-icon
40 210
📌 The Evolution of Text to Video Models 🗂 Category: DEEP LEARNING 🕒 Date: 2024-09-19 | ⏱️ Read time: 10 min read Simplifyi
📌 The Evolution of Text to Video Models 🗂 Category: DEEP LEARNING 🕒 Date: 2024-09-19 | ⏱️ Read time: 10 min read Simplifying the neural nets behind Generative Video Diffusion

Machine Learning
Machine Learningverified-telegram-icon
40 210
📌 AdEMAMix: A Deep Dive into a New Optimizer for Your Deep Neural Network 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-09-19
📌 AdEMAMix: A Deep Dive into a New Optimizer for Your Deep Neural Network 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-09-19 | ⏱️ Read time: 15 min read A better and faster option than the ADAM optimizer, from Apple Research

Machine Learning
Machine Learningverified-telegram-icon
40 210
No skills? No problem. Just copy-paste and GET PAID. ➡️ 22,000+ already started… YOU'RE NEXT! Click here @NPFXSignals #ad InsideAds

Machine Learning
Machine Learningverified-telegram-icon
40 210
📌 Shared Nearest Neighbors: A More Robust Distance Metric 🗂 Category: 🕒 Date: 2024-09-19 | ⏱️ Read time: 36 min read A dis
📌 Shared Nearest Neighbors: A More Robust Distance Metric 🗂 Category: 🕒 Date: 2024-09-19 | ⏱️ Read time: 36 min read A distance metric that can improve prediction, clustering, and outlier detection in datasets with many…

Machine Learning
Machine Learningverified-telegram-icon
40 210
📌 Improving Code Quality with Array and DataFrame Type Hints 🗂 Category: 🕒 Date: 2024-09-19 | ⏱️ Read time: 12 min read Ho
📌 Improving Code Quality with Array and DataFrame Type Hints 🗂 Category: 🕒 Date: 2024-09-19 | ⏱️ Read time: 12 min read How generic specification permits powerful static and runtime validation

Machine Learning
Machine Learningverified-telegram-icon
40 210
📌 Through the Uncanny Mirror: Do LLMs Remember Like the Human Mind? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-09-19
📌 Through the Uncanny Mirror: Do LLMs Remember Like the Human Mind? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-09-19 | ⏱️ Read time: 10 min read Exploring the Eerie Parallels and Profound Differences Between AI and Human Memory

Machine Learning
Machine Learningverified-telegram-icon
40 210
📌 Mastering t-SNE: A Comprehensive Guide to Understanding and Implementation in Python 🗂 Category: DATA SCIENCE 🕒 Date: 20
📌 Mastering t-SNE: A Comprehensive Guide to Understanding and Implementation in Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-20 | ⏱️ Read time: 26 min read Unlock the power of t-SNE for visualizing high-dimensional data, with a step-by-step Python implementation and…

Machine Learning
Machine Learningverified-telegram-icon
40 210
📌 Choosing Between LLM Agent Frameworks 🗂 Category: 🕒 Date: 2024-09-20 | ⏱️ Read time: 15 min read Thanks to John Gilhuly
📌 Choosing Between LLM Agent Frameworks 🗂 Category: 🕒 Date: 2024-09-20 | ⏱️ Read time: 15 min read Thanks to John Gilhuly for his contributions to this piece. Agents are having a moment.…

Machine Learning
Machine Learningverified-telegram-icon
40 210
📌 Paper Walkthrough: U-Net 🗂 Category: DEEP LEARNING 🕒 Date: 2024-09-20 | ⏱️ Read time: 16 min read A PyTorch implementati
📌 Paper Walkthrough: U-Net 🗂 Category: DEEP LEARNING 🕒 Date: 2024-09-20 | ⏱️ Read time: 16 min read A PyTorch implementation on one of the most popular semantic segmentation models.