Artificial Intelligence
رفتن به کانال در Telegram
🔰 Machine Learning & Artificial Intelligence Free Resources 🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more For Promotions: @love_data
نمایش بیشتر
📈 تحلیل کانال تلگرام Artificial Intelligence
کانال Artificial Intelligence (@machinelearning_deeplearning) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 56 625 مشترک است و جایگاه 3 064 را در دسته آموزش و رتبه 5 904 را در منطقه الهند دارد.
📊 شاخص‌های مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 56 625 مشترک جذب کرده است.
بر اساس آخرین داده‌ها در تاریخ 01 نوامبر, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 423 و در ۲۴ ساعت گذشته برابر 15 بوده و همچنان دسترسی گسترده‌ای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 4.48% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 1.54% واکنش نسبت به کل مشترکان کسب می‌کند.
- دسترسی پست‌ها: هر پست به طور میانگین 2 534 بازدید دریافت می‌کند. در اولین روز معمولاً 874 بازدید جمع‌آوری می‌شود.
- واکنش‌ها و تعامل: مخاطبان به‌طور فعال حمایت می‌کنند؛ میانگین واکنش به هر پست 13 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند learning, classification, layer, pattern, chatbot تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاه‌های شخصی توصیف می‌کند:
“🔰 Machine Learning & Artificial Intelligence Free Resources
🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more
For Promotions: @love_data”
به لطف به‌روزرسانی‌های پرتکرار (آخرین داده در تاریخ 02 نوامبر, 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.
56 625
مشترکین
+1524 ساعت
+737 روز
+42330 روز
آرشیو پست ها
56 625
Here are the top 5 machine learning projects that are suitable for freshers to work on:
1. Predicting House Prices: Build a machine learning model that predicts house prices based on features such as location, size, number of bedrooms, etc. This project will help you understand regression techniques and feature engineering.
2. Image Classification: Create a model that can classify images into different categories such as cats vs. dogs, fruits, or handwritten digits. This project will introduce you to convolutional neural networks (CNNs) and image processing.
3. Sentiment Analysis: Develop a sentiment analysis model that can classify text data as positive, negative, or neutral. This project will help you learn natural language processing techniques and text classification algorithms.
4. Credit Card Fraud Detection: Build a model that can detect fraudulent credit card transactions based on transaction data. This project will help you understand anomaly detection techniques and imbalanced classification problems.
5. Recommendation System: Create a recommendation system that suggests products or movies to users based on their preferences and behavior. This project will introduce you to collaborative filtering and recommendation algorithms.
These projects will not only enhance your machine learning skills but also provide you with practical experience in working on real-world data science problems.
56 625
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Book: 📚Exercises in Machine Learning
Authors: Michael U. Gutmann
year: 2024
pages: 211
56 625
Want to build AI Apps and get jobs in GenAI domain? 🚀
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🚓 Deep Learning Roadmap 2024- Step-by-Step Career Path
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