AI and Machine Learning
Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more! Buy ads: https://telega.io/c/machine_learning_courses
إظهار المزيد📈 نظرة تحليلية على قناة تيليجرام AI and Machine Learning
تُعد قناة AI and Machine Learning (@machine_learning_courses) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 95 141 مشتركاً، محتلاً المرتبة 1 512 في فئة التعليم والمرتبة 3 036 في منطقة الهند.
📊 مؤشرات الجمهور والحراك
منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 95 141 مشتركاً.
بحسب آخر البيانات بتاريخ 25 أغسطس, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 335، وفي آخر 24 ساعة بمقدار -23، مع بقاء الوصول العام مرتفعاً.
- حالة التحقق: غير موثّقة
- معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 10.63%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 2.44% من ردود الفعل نسبةً إلى إجمالي المشتركين.
- وصول المنشورات: يحصل كل منشور على متوسط 10 117 مشاهدة. وخلال اليوم الأول يجمع عادةً 2 325 مشاهدة.
- التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 18.
- الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل learning, llm, linkedin, linux, udemy.
📝 الوصف وسياسة المحتوى
يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
“Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more!
Buy ads: https://telega.io/c/machine_learning_courses”
بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 26 أغسطس, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التعليم.
جاري تحميل البيانات...
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| 2 | 100 AI ML projects for all levels | 2 737 |
| 3 | 📱Artificial intelligence
📱A Content Marketer's Guide to Responsible AI | 4 737 |
| 4 | 🔅 A Content Marketer's Guide to Responsible AI
📝 Learn to use AI responsibly in content marketing, balancing personalization, privacy, and ethical AI practices.
🌐 Author: Lauren Diethelm
🔰 Level: General
⏰ Duration: 23m
📋 Topics: Content Marketing, Artificial Intelligence for Business
🔗 Join Artificial intelligence for more courses | 4 577 |
| 5 | AI Agents vs Agentic AI... what’s the actual difference?
There are 3 types of AI workflows worth knowing and each performs a different task. If you don’t understand these you’re probably falling behind.
Non-Agentic AI:
Basic prompt-response AI with no memory/reasoning.
They’re fast, cheap, and universally accessible, requires no technical build or integration and great for clear, one-off tasks.
Agentic AI:
Self-managing AI system that can plan and execute.
Great for handling complex, changing projects. They can integrate with tools and databases and produce more reliable outcomes.
AI Agent:
A single-task AI worker designed to automate one task.
Automates repetitive, time-consuming tasks, quick setup and cost-efficient and easy to test and refine within roles
In short:
AI Agents = Single-task automation
Agentic AI = Multi-step problem solving | 6 265 |
| 6 | AI Concepts Explained | 6 732 |
| 7 | 💡 Your Gateway to Exclusive Content
🔐 What is The Premium Vault?
We are a private Telegram channel dedicated to delivering high-quality, premium content that you simply cannot find through ordinary searches, free platforms, or standard telegram channels. Every piece of content inside this vault is carefully collected, researched, and created exclusively for our members.
📦 What’s Inside?
1⃣ Tutorials, and resources across various premium sites
🔢 Movies, TV Shows and Documentaries
🔢 Premium Applications, fully featured, paid-tier software and productivity tools
〰️〰️〰️〰️〰️〰️〰️〰️〰️
🚫 What You Won't Find Here:
No recycled freebies. No low-effort posts. No clickbait. Everything inside The Premium Vault is original, valuable, or rare — shared only with our inner circle of premium subscribers.
🔗 https://t.me/ThePremiumVault/4 | 6 111 |
| 8 | AI Engineer Roadmap | 9 009 |
| 9 | 📱Artificial intelligence
📱Building Agentic AI Systems | 10 014 |
| 10 | 🔅 Building Agentic AI Systems
📝 Gain the knowledge and practical skills required to design and develop an Agentic AI system.
🌐 Author: Rashim Mogha
🔰 Level: Intermediate
⏰ Duration: 1h 2m
📋 Topics: AI Software Development, AI Agents
🔗 Join Artificial intelligence for more courses | 9 888 |
| 11 | Most Data Scientists structure their projects wrong.
Use this clean, production-ready layout👇
1️⃣ config/ – config files
Separate params from code (local.yaml, prod.yaml)
2️⃣ data/ – full data lifecycle
raw → preprocessed → features → predictions
3️⃣ entrypoint/ – main scripts
train.py (pipeline)
inference.py (batch/real-time)
4️⃣ notebooks/ – exploration only
EDA, analysis — never production logic
5️⃣ src/ – core ML code
feature engineering, training, inference (modular + testable)
6️⃣ tests/ – automated checks
prevent silent failures
7️⃣ docker + env files – reproducibility
same setup on any machine/CI
8️⃣ pinned dependencies – stability
exact versions → consistent results | 9 691 |
| 12 | 4 stages of LLM Training | 11 038 |
| 13 | Key Nodes in n8n
Most people think AI automation is complex, but with n8n it comes down to just 7 building blocks.
1️⃣ Code Node → custom logic
2️⃣ HTTP Request → connect any API
3️⃣ Edit Fields → clean data
4️⃣ IF Node → conditional paths
5️⃣ Switch Node → handle multiple cases
6️⃣ Loop Over Items → process lists
7️⃣ Error Handling → keep workflows alive
n8n makes it simple: drag, drop, connect. | 13 306 |
| 14 | 📱Artificial intelligence
📱Hands-On AI: Building Your First LLM-Powered App | 11 815 |
| 15 | 🔅 Hands-On AI: Building Your First LLM-Powered App
📝 Get started building apps powered by large language models (LLMs) in this hands-on, skills-based course for beginners.
🌐 Author: Han-chung Lee
🔰 Level: Beginner
⏰ Duration: 1h 14m
📋 Topics: AI Software Development, Large Language Models, Artificial Intelligence
🔗 Join Artificial intelligence for more courses | 11 233 |
| 16 | All major LLMs, one login: glbgpt.com
GPT-5 · Claude · Gemini · Grok · DeepSeek. Crypto top-up (USDT), pay-as-you-go, no sub required.
→ https://tglink.io/ad3c29e3f95e5e | 3 134 |
| 17 | 📕 The Ultimate Roadmap to master AI Agents | 14 024 |
| 18 | 🔢 Stages of LLM Training
Training a Large Language Model isn’t a single step—it’s a journey through multiple stages that shape how it understands, follows, and reasons.
Here’s the progression:
Stage 0 → A randomly initialized model, just noise with potential.
Stage 1 → Pre-Training, where it absorbs patterns from massive text data.
Stage 2 → Instruction Fine-Tuning, aligning it to follow human-written instructions.
Stage 3 → Preference Fine-Tuning, refining it to generate responses people actually prefer.
Stage 4 → Reasoning Fine-Tuning, pushing it to think more logically and solve complex problems.
From raw parameters to advanced reasoning, each stage transforms the model into something smarter, more helpful, and more aligned with human goals. | 13 197 |
| 19 | 🧠 Code with an AI agent — inside Telegram
BrainDaemon is a private AI coding workspace (Mini App):
• Cloud machine + real tools per chat
• Build multi-file projects, not just paste snippets
• Live reasoning while it works with you
Open the Mini App and start building:
👉 https://t.me/BrainDaemonBot | 2 153 |
| 20 | 🔢 Layers of LLM Stack | 14 280 |
