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
Сеть:📈 Аналитический обзор Telegram-канала Machine Learning
Канал Machine Learning (@machinelearning9) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 40 291 подписчиков, занимая 3 341 место в категории Технологии и приложения и 226 место в регионе Сирия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 40 291 подписчиков.
Согласно последним данным от 08 июля, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 353, а за последние 24 часа — 12, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 2.31%. В первые 24 часа после публикации контент обычно набирает 1.90% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 929 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 09 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.
40 291
Подписчики
+1224 часа
+867 дней
+35330 день
Архив постов
40 307
📌 No Peeking Ahead: Time-Aware Graph Fraud Detection
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-09-14 | ⏱️ Read time: 15 min read
How to implement leak-free graph fraud detection
40 307
What if you could unlock the secrets behind every glass of wine you sip? Discover rare finds, honest reviews, and the fascinating stories of wine regions — without the snobbery. Whether you’re a connoisseur or simply love exploring new tastes, join Simply Wine | Great Wine Lover for insights you won’t find anywhere else. Ready to swirl, sniff, and savor? Dive in now!
#ad InsideAds
40 307
📌 Roadmap to Becoming a Data Scientist, Part 3: Machine Learning
🗂 Category: CAREER ADVICE
🕒 Date: 2025-01-14 | ⏱️ Read time: 11 min read
From beginner to pro: key machine learning skills for data science aspirants
40 307
📌 Using Optimization to Solve Adversarial Problems
🗂 Category:
🕒 Date: 2025-01-14 | ⏱️ Read time: 41 min read
An example of simultaneously optimizing two policies for two adversarial agents, looking specifically at the…
40 307
📌 You Think 80% Means 80%? Why Prediction Probabilities Need a Second Look
🗂 Category:
🕒 Date: 2025-01-14 | ⏱️ Read time: 9 min read
Understand the gap between predicted probabilities and real-world outcomes
40 307
📌 From Darwin to Deep Work
🗂 Category: DATA SCIENCE
🕒 Date: 2025-01-14 | ⏱️ Read time: 7 min read
Focus Strategies for Machine Learning Practitioners
40 307
📌 Awesome Plotly with Code Series (Part 8): How to Balance Dominant Bar Chart Categories
🗂 Category: DATA SCIENCE
🕒 Date: 2025-01-14 | ⏱️ Read time: 8 min read
Discover the #1 strategy to handle skyscraper bars in your charts
40 307
📌 Why Normalization Is Crucial for Policy Evaluation in Reinforcement Learning
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-01-14 | ⏱️ Read time: 6 min read
Enhancing Accuracy in Reinforcement Learning Policy Evaluation through Normalization
40 307
📌 Scale Experiment Decision-Making with Programmatic Decision Rules
🗂 Category: DATA SCIENCE
🕒 Date: 2025-01-14 | ⏱️ Read time: 6 min read
Decide what to do with experiment results in code
40 307
📌 How To: Forecast Time Series Using Lags
🗂 Category: DATA SCIENCE
🕒 Date: 2025-01-14 | ⏱️ Read time: 8 min read
Lag columns can significantly boost your model’s performance
40 307
📌 Hands-On Delivery Routes Optimization (TSP) with AI, Using LKH and Python
🗂 Category: DATA SCIENCE
🕒 Date: 2025-01-14 | ⏱️ Read time: 12 min read
Here’s how to optimize the delivery routes, from theory to code.
40 307
📌 Basics of GANs & SMOTE for Data Augmentation
🗂 Category: DATA SCIENCE
🕒 Date: 2025-01-15 | ⏱️ Read time: 14 min read
GANs and SMOTE Explained with Bartending: Data Science for Machine Learning Series (1)
40 307
📌 Scaling Segmentation with Blender: How to Automate Dataset Creation
🗂 Category: DATA SCIENCE
🕒 Date: 2025-01-15 | ⏱️ Read time: 10 min read
A Step-by-Step Guide to Generating Synthetic Data for Training AI Models
40 307
📌 LossVal Explained: Efficiently Estimate the Importance of Your Training Data
🗂 Category: DATA SCIENCE
🕒 Date: 2025-01-15 | ⏱️ Read time: 7 min read
How to Exploit the Loss Function for Efficient Data Valuation
40 307
📌 Recursive Walks down User Referral Trees
🗂 Category: MARKETING
🕒 Date: 2025-01-15 | ⏱️ Read time: 6 min read
Measuring the total influence of users in a user referral program by traversing indirect referrals
40 307
📌 Unlocking the Power of Machine Learning in Analytics: Practical Use Cases and Skills
🗂 Category: ANALYTICS
🕒 Date: 2025-01-15 | ⏱️ Read time: 9 min read
Your essential machine learning checklist to excel as a data scientist in analytics
40 307
📌 Understanding Flash Attention: Writing the Algorithm from Scratch in Triton
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2025-01-15 | ⏱️ Read time: 7 min read
Find out how Flash Attention works. Afterward, we’ll refine our understanding by writing a GPU…
40 307
Ever wondered how top traders spot the next crypto pump — before everyone else? Unlock the power of pure technical analysis with CRYPTO LEGENDS. Get real-time charts, key altcoin & BTC signals, and actionable insights — no hype, just facts. Be first to catch market moves right here. Don’t just watch the charts — use them. Join now for a real edge!
#إعلان InsideAds
40 307
📌 What Did I Learn from Building LLM Applications in 2024? – Part 2
🗂 Category:
🕒 Date: 2025-01-17 | ⏱️ Read time: 13 min read
An engineer’s journey to building LLM-powered applications
40 307
📌 Influential Time-Series Forecasting Papers of 2023-2024: Part 1
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2025-01-17 | ⏱️ Read time: 16 min read
Exploring the latest advancements in time series
