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
شبکه:📈 تحلیل کانال تلگرام Machine Learning
کانال Machine Learning (@machinelearning9) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 40 373 مشترک است و جایگاه 3 327 را در دسته فناوری و برنامهها و رتبه 225 را در منطقه سوريا دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 40 373 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 12 ژوئیه, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 399 و در ۲۴ ساعت گذشته برابر 24 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 2.42% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 1.74% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 979 بازدید دریافت میکند. در اولین روز معمولاً 703 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 4 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 13 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.
40 373
مشترکین
+2424 ساعت
+1257 روز
+39930 روز
آرشیو پست ها
40 393
📌 A Visual Guide to Tuning Random Forest Hyperparameters
🗂 Category: DATA SCIENCE
🕒 Date: 2025-09-04 | ⏱️ Read time: 8 min read
How hyperparameter tuning visually changes random forests
40 393
📌 Should We Use LLMs As If They Were Swiss Knives?
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2025-09-04 | ⏱️ Read time: 9 min read
A logic game performance comparison between popular LLMs and a custom-made algorithm
40 393
📌 Tool Masking: The Layer MCP Forgot
🗂 Category: AGENTIC AI
🕒 Date: 2025-09-05 | ⏱️ Read time: 16 min read
Tool masking for AI improves AI agents: shape MCP tool surfaces to cut tokens and…
40 393
📌 Zero-Inflated Data: A Comparison of Regression Models
🗂 Category: DATA SCIENCE
🕒 Date: 2025-09-05 | ⏱️ Read time: 13 min read
How to detect it and which model to choose.
40 393
📌 AI Operations Under the Hood: Challenges and Best Practices
🗂 Category: LLM APPLICATIONS
🕒 Date: 2025-09-05 | ⏱️ Read time: 18 min read
Building robust, reproducible, and reliable GenAI applications requires a framework of continuous improvement, rigorous evaluation,…
40 393
📌 Showcasing Your Work on HuggingFace Spaces
🗂 Category: PRODUCTIVITY
🕒 Date: 2025-09-05 | ⏱️ Read time: 9 min read
Building an app is exciting – but sharing it is where the real value kicks…
40 393
📌 How to Context Engineer to Optimize Question Answering Pipelines
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-09-05 | ⏱️ Read time: 9 min read
Learn how to apply context engineering to enhance your question answering systems.
40 393
📌 Tool Masking: The Layer MCP Forgot
🗂 Category: AGENTIC AI
🕒 Date: 2025-09-05T07:00:00-05:00 | ⏱ Read time: 16 min read
Tool masking for AI improves AI agents: shape MCP tool surfaces to cut tokens and…
40 393
📌 Zero-Inflated Data: A Comparison of Regression Models
🗂 Category: DATA SCIENCE
🕒 Date: 2025-09-05T08:30:00-05:00 | ⏱ Read time: 13 min read
How to detect it and which model to choose.
40 393
📌 AI Operations Under the Hood: Challenges and Best Practices
🗂 Category: LLM APPLICATIONS
🕒 Date: 2025-09-05T10:00:00-05:00 | ⏱ Read time: 18 min read
Building robust, reproducible, and reliable GenAI applications requires a framework of continuous improvement, rigorous evaluation,…
40 393
📌 Showcasing Your Work on HuggingFace Spaces
🗂 Category: PRODUCTIVITY
🕒 Date: 2025-09-05T11:30:00-05:00 | ⏱ Read time: 9 min read
Building an app is exciting – but sharing it is where the real value kicks…
40 393
📌 How to Context Engineer to Optimize Question Answering Pipelines
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-09-05T12:30:00-05:00 | ⏱ Read time: 9 min read
Learn how to apply context engineering to enhance your question answering systems.
40 393
Repost from Github Top Repositories
🔥 Trending Repository: ML-From-Scratch
📝 Description: Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
🔗 Repository URL: https://github.com/eriklindernoren/ML-From-Scratch
📖 Readme: https://github.com/eriklindernoren/ML-From-Scratch#readme
📊 Statistics:
🌟 Stars: 27.8K stars
👀 Watchers: 951
🍴 Forks: 4.8K forks
💻 Programming Languages: Python
🏷️ Related Topics:
#data_science #machine_learning #data_mining #deep_learning #genetic_algorithm #deep_reinforcement_learning #machine_learning_from_scratch================================== 🧠 By: https://t.me/DataScienceM
40 393
No one believed I could double my portfolio in just 30 days… but then I discovered the Prop Mastery tricks top traders keep secret. Want to know how? The real strategies are hidden right here — and only a few catch on before it’s too late!
#إعلان InsideAds
40 393
“I was laughed at when I bought crypto in 2019. Now my portfolio’s up 1200% — and friends keep asking for ‘the secret’…
But nobody talks about the brutal truths I learned along the way. Want to see what everyone’s missing? 👉 See it here
#إعلان InsideAds
40 393
Think you know your football history?
Who scored a hat-trick against Real Madrid in yellow and black?
Every day, Footy Riddles ⚽ drops clever puzzles about iconic players, unforgettable moments, and legendary matches.
Challenge your football brain and see if you can guess before anyone else!
Only the quickest fans know all the answers—are you one of them?
#إعلان InsideAds
40 393
90% трейдеров сливают из-за ручного анализа и эмоций?
TRUE — первый AI-протокол на Solana, который сам учится на on-chain данных, выдает персональные стратегии и делает трейдинг понятным на естественном языке.
Именно сейчас можно получить доступ к запуску и участвовать в токенсейле $TRUE, пока условия максимально выгодные.
Трейдинг будущего начинается здесь — не упусти шанс быть первым! Присоединяйся
#إعلان InsideAds
40 393
What if you could skip all the chart noise and just ask AI to invest for you?
90% of traders lose money… but the game changes when you chat instead of chart.
Be early—join the AI revolution before everyone else wakes up.
#إعلان InsideAds
40 393
🔥 Trending Repository: abogen
📝 Description: Generate audiobooks from EPUBs, PDFs and text with synchronized captions.
🔗 Repository URL: https://github.com/denizsafak/abogen
🌐 Website: https://pypi.org/project/abogen/
📖 Readme: https://github.com/denizsafak/abogen#readme
📊 Statistics:
🌟 Stars: 3.1K stars
👀 Watchers: 18
🍴 Forks: 159 forks
💻 Programming Languages: Python - Batchfile - Dockerfile
🏷️ Related Topics:
#text_to_speech #audiobook #tts #speech_synthesis #subtitles #audiobooks #narrator #content_creator #voice_synthesis #epub_converter #kokoro #content_creation #text_to_audio #media_generation #kokoro_tts #kokoro_82m================================== 🧠 By: https://t.me/DataScienceM
40 393
🔥 Trending Repository: cognitive-load
📝 Description: 🧠 Cognitive Load is what matters
🔗 Repository URL: https://github.com/zakirullin/cognitive-load
📖 Readme: https://github.com/zakirullin/cognitive-load#readme
📊 Statistics:
🌟 Stars: 9.4K stars
👀 Watchers: 86
🍴 Forks: 200 forks
💻 Programming Languages: Not available
🏷️ Related Topics: Not available
==================================
🧠 By: https://t.me/DataScienceM
