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
Mostrar más📈 Análisis del canal de Telegram AI and Machine Learning
El canal AI and Machine Learning (@machine_learning_courses) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 95 141 suscriptores, ocupando la posición 1 512 en la categoría Educación y el puesto 3 036 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 95 141 suscriptores.
Según los últimos datos del 25 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 335, y en las últimas 24 horas de -23, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 10.63%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 2.44% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 10 117 visualizaciones. En el primer día suele acumular 2 325 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 18.
- Intereses temáticos: El contenido se centra en temas clave como learning, llm, linkedin, linux, udemy.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more!
Buy ads: https://telega.io/c/machine_learning_courses”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 26 agosto, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Educación.
95 141
Suscriptores
-2324 horas
+107 días
+33530 días
Archivo de publicaciones
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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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+6
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
