fa
Feedback
Machine Learning

Machine Learning

رفتن به کانال در Telegram

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

نمایش بیشتر

📈 تحلیل کانال تلگرام Machine Learning

کانال Machine Learning (@machinelearning9) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 40 273 مشترک است و جایگاه 3 347 را در دسته فناوری و برنامه‌ها و رتبه 227 را در منطقه سوريا دارد.

📊 شاخص‌های مخاطب و پویایی

از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 40 273 مشترک جذب کرده است.

بر اساس آخرین داده‌ها در تاریخ 07 ژوئیه, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 352 و در ۲۴ ساعت گذشته برابر 21 بوده و همچنان دسترسی گسترده‌ای حفظ شده است.

  • وضعیت تأیید: تأیید نشده
  • نرخ تعامل (ER): میانگین تعامل مخاطب 2.23% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 1.88% واکنش نسبت به کل مشترکان کسب می‌کند.
  • دسترسی پست‌ها: هر پست به طور میانگین 896 بازدید دریافت می‌کند. در اولین روز معمولاً 758 بازدید جمع‌آوری می‌شود.
  • واکنش‌ها و تعامل: مخاطبان به‌طور فعال حمایت می‌کنند؛ میانگین واکنش به هر پست 3 است.
  • علایق موضوعی: محتوا بر موضوعات کلیدی مانند distance, insidead, gpu, learning, degree تمرکز دارد.

📝 توضیح و سیاست محتوایی

نویسنده این فضا را محل بیان دیدگاه‌های شخصی توصیف می‌کند:
Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho

به لطف به‌روزرسانی‌های پرتکرار (آخرین داده در تاریخ 08 ژوئیه, 2026)، کانال همواره به‌روز و دارای دسترسی بالاست. تحلیل‌ها نشان می‌دهد مخاطبان به‌طور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته فناوری و برنامه‌ها تبدیل کرده‌اند.

40 273
مشترکین
+2124 ساعت
+957 روز
+35230 روز
آرشیو پست ها
What if you could unlock the secrets behind every glass of wine you sip? Discover rare finds, honest reviews, and the fascina
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

📌 Roadmap to Becoming a Data Scientist, Part 3: Machine Learning 🗂 Category: CAREER ADVICE 🕒 Date: 2025-01-14 | ⏱️ Read ti
📌 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

📌 Using Optimization to Solve Adversarial Problems 🗂 Category: 🕒 Date: 2025-01-14 | ⏱️ Read time: 41 min read An example o
📌 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…

📌 You Think 80% Means 80%? Why Prediction Probabilities Need a Second Look 🗂 Category: 🕒 Date: 2025-01-14 | ⏱️ Read time:
📌 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

📌 From Darwin to Deep Work 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-14 | ⏱️ Read time: 7 min read Focus Strategies for Mac
📌 From Darwin to Deep Work 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-14 | ⏱️ Read time: 7 min read Focus Strategies for Machine Learning Practitioners

📌 Awesome Plotly with Code Series (Part 8): How to Balance Dominant Bar Chart Categories 🗂 Category: DATA SCIENCE 🕒 Date:
📌 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

📌 Why Normalization Is Crucial for Policy Evaluation in Reinforcement Learning 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-0
📌 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

📌 Scale Experiment Decision-Making with Programmatic Decision Rules 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-14 | ⏱️ Read
📌 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

📌 How To: Forecast Time Series Using Lags 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-14 | ⏱️ Read time: 8 min read Lag colum
📌 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

📌 Hands-On Delivery Routes Optimization (TSP) with AI, Using LKH and Python 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-14 |
📌 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.

📌 Basics of GANs & SMOTE for Data Augmentation 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-15 | ⏱️ Read time: 14 min read GAN
📌 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)

📌 Scaling Segmentation with Blender: How to Automate Dataset Creation 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-15 | ⏱️ Rea
📌 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

📌 LossVal Explained: Efficiently Estimate the Importance of Your Training Data 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-15
📌 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

📌 Recursive Walks down User Referral Trees 🗂 Category: MARKETING 🕒 Date: 2025-01-15 | ⏱️ Read time: 6 min read Measuring t
📌 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

📌 Unlocking the Power of Machine Learning in Analytics: Practical Use Cases and Skills 🗂 Category: ANALYTICS 🕒 Date: 2025-
📌 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

📌 Understanding Flash Attention: Writing the Algorithm from Scratch in Triton 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date:
📌 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…

Ever wondered how top traders spot the next crypto pump — before everyone else? Unlock the power of pure technical analysis w
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

📌 What Did I Learn from Building LLM Applications in 2024? – Part 2 🗂 Category: 🕒 Date: 2025-01-17 | ⏱️ Read time: 13 min
📌 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

📌 Influential Time-Series Forecasting Papers of 2023-2024: Part 1 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-01-17 |
📌 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

📌 Preparing PDFs for RAGs 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-17 | ⏱️ Read time: 5 min read I created a graph storage
📌 Preparing PDFs for RAGs 🗂 Category: DATA SCIENCE 🕒 Date: 2025-01-17 | ⏱️ Read time: 5 min read I created a graph storage from dozens of annual reports (with tables)