Machine Learning with Python
رفتن به کانال در Telegram
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho
نمایش بیشتر
شبکه:📈 تحلیل کانال تلگرام Machine Learning with Python
کانال Machine Learning with Python (@codeprogrammer) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 68 536 مشترک است و جایگاه 2 402 را در دسته آموزش و رتبه 4 600 را در منطقه الهند دارد.
📊 شاخص‌های مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 68 536 مشترک جذب کرده است.
بر اساس آخرین داده‌ها در تاریخ 29 اکتبر, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 74 و در ۲۴ ساعت گذشته برابر -5 بوده و همچنان دسترسی گسترده‌ای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 3.84% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 1.47% واکنش نسبت به کل مشترکان کسب می‌کند.
- دسترسی پست‌ها: هر پست به طور میانگین 2 629 بازدید دریافت می‌کند. در اولین روز معمولاً 1 007 بازدید جمع‌آوری می‌شود.
- واکنش‌ها و تعامل: مخاطبان به‌طور فعال حمایت می‌کنند؛ میانگین واکنش به هر پست 9 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند insidead, learning, degree, evaluation, algorithm تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاه‌های شخصی توصیف می‌کند:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
Admin: @HusseinSheikho || @Hussein_Sheikho”
به لطف به‌روزرسانی‌های پرتکرار (آخرین داده در تاریخ 30 اکتبر, 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 آموزش تبدیل کرده‌اند.
68 536
مشترکین
-524 ساعت
-847 روز
+7430 روز
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Дмитрий Мачихин, основатель компании BitOK (Бит окей). Предприниматель и инвестор в сфере финансов, web3 и игр. Пишу для себя и для вас. Иногда наступаю на горло мошенникам и врагам народа.
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Repost from Udemy Free
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https://t.me/jobsandinternshipsupdates
💛 Top 10 Best Websites to Learn Machine Learning ⭐️
by [@codeprogrammer]
---
🧠 Google’s ML Course
🔗 https://developers.google.com/machine-learning/crash-course
📈 Kaggle Courses
🔗 https://kaggle.com/learn
🧑🎓 Coursera – Andrew Ng’s ML Course
🔗 https://coursera.org/learn/machine-learning
⚡️ Fast.ai
🔗 https://fast.ai
🔧 Scikit-Learn Documentation
🔗 https://scikit-learn.org
📹 TensorFlow Tutorials
🔗 https://tensorflow.org/tutorials
🔥 PyTorch Tutorials
🔗 https://docs.pytorch.org/tutorials/
🏛️ MIT OpenCourseWare – Machine Learning
🔗 https://ocw.mit.edu/courses/6-867-machine-learning-fall-2006/
✍️ Towards Data Science (Blog)
🔗 https://towardsdatascience.com
---
💡 Which one are you starting with? Drop a comment below! 👇
#MachineLearning #LearnML #DataScience #AI #TechWithRam
Do you see yourself as a programmer, researcher, or engineer?
Repost from Machine Learning with Python
+1
These Google Colab-notebooks help to implement all machine learning algorithms from scratch 🤯
Repo: https://udlbook.github.io/udlbook/
👉 @codeprogrammer
Build your own AI agent from scratch for free in 5 minutes
In this article, I will show you how to build your first AI agent from scratch using Google’s ADK (Agent Development Kit). This is an open-source framework that makes it easier to create agents, test them, add tools, and even build multi-agent systems.
Read: https://habr.com/en/articles/974212/
Repost from Data Analytics
This repository collects everything you need to use AI and LLM in your projects.
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Repo: https://github.com/KalyanKS-NLP/llm-engineer-toolkit
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