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 41 086 مشترک است و جایگاه 3 179 را در دسته فناوری و برنامهها و رتبه 218 را در منطقه سوريا دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 41 086 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 02 سپتامبر, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 300 و در ۲۴ ساعت گذشته برابر 23 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 2.75% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 1.89% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 1 129 بازدید دریافت میکند. در اولین روز معمولاً 777 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 03 سپتامبر, 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.
41 086
مشترکین
+2324 ساعت
+987 روز
+30030 روز
آرشیو پست ها
41 089
Repost from Remote Jobs — Daily LinkedIn Picks 💼
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41 089
Repost from Machine Learning with Python
🧿ANTHROPH\C Launches 13 Free AI Courses
Anthropic Academy has announced 13 free AI courses. The courses cover the following topics:
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41 089
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41 089
Repost from Machine Learning with Python
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Repost from Machine Learning with Python
🔖 A comprehensive collection of resources on MLOps
We've found a useful collection for those who want to go beyond just training models and delve into their deployment and operation.
This repository contains the best materials on deploying, monitoring, automating ML pipelines, CI/CD, and other practices that are essential for production systems.
⛓ Link to GitHub
https://github.com/visenger/awesome-mlops
41 089
Repost from Python Courses & Resources
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"Introduction to Machine Learning" is another free textbook on machine learning, approximately 600 pages long, which emphasizes a deep mathematical understanding of the subject. 📚🧮
The book begins with the mathematical foundations necessary for further study: linear algebra, mathematical analysis, probability theory, matrix analysis, and optimization methods. It then covers the main supervised learning algorithms: linear and logistic regression, the k-nearest neighbors method, decision trees, random forests, boosting, and neural networks. 🤖📈
A significant portion of the book is dedicated to probabilistic and generative models. It discusses Monte Carlo methods, graphical models, Bayesian networks, variational methods, normalizing flows, variational autoencoders (VAEs), and generative adversarial networks (GANs). 🎲🧠
The final chapters discuss clustering, principal component analysis (PCA), learning on manifolds, and theoretical estimates of a model's ability to generalize. 🔍📊
In my opinion, this is an excellent resource for those who want to gain a broad understanding of machine learning and understand the mathematics underlying the key methods, rather than treating them as "black boxes." 💡✨
https://arxiv.org/pdf/2409.02668
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Repost from Machine Learning with Python
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Repost from Machine Learning with Python
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