AI and Machine Learning
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Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more! Buy ads: https://telega.io/c/machine_learning_courses
Больше📈 Аналитический обзор Telegram-канала AI and Machine Learning
Канал AI and Machine Learning (@machine_learning_courses) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 95 141 подписчиков, занимая 1 512 место в категории Образование и 3 036 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 95 141 подписчиков.
Согласно последним данным от 25 августа, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 335, а за последние 24 часа — -23, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 10.63%. В первые 24 часа после публикации контент обычно набирает 2.44% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 10 117 просмотров. В течение первых суток публикация набирает 2 325 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 18.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как learning, llm, linkedin, linux, udemy.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more!
Buy ads: https://telega.io/c/machine_learning_courses”
Благодаря высокой частоте обновлений (последние данные получены 26 августа, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Образование.
95 141
Подписчики
-2324 часа
+107 дней
+33530 день
Архив постов
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🔅 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
95 141
+1
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
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💡 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
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🔅 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
95 141
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
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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.
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🔅 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
95 141
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
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🔢 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.
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🧠 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
