¡Ya disponible! Investigación de Telegram 2025 — los principales insights del año 
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 94 021 suscriptores, ocupando la posición 1 561 en la categoría Educación y el puesto 3 020 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 94 021 suscriptores.
Según los últimos datos del 24 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 986, y en las últimas 24 horas de 67, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 6.50%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.56% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 6 109 visualizaciones. En el primer día suele acumular 1 470 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 8.
- 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 25 junio, 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.
94 021
Suscriptores
+6724 horas
+1517 días
+98630 días
Archivo de publicaciones
94 035
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📝 New research on text creativity
Scientists have shown: texts created by humans are semantically newer than those generated by AI.
🔎 How it was measured
They introduced the metric "semantic novelty" — the cosine distance between adjacent sentences.
🧠 Main findings
Human texts consistently show higher novelty across different embedding models (RoBERTa, DistilBERT, MPNet, MiniLM).
In the "human-AI storytelling" dataset, the human contribution was semantically more diverse.
✨ But there is a nuance
What we call AI "hallucinations" can be useful in collaborative storytelling. They add unexpected twists and help maintain interest in the story.
👉 Conclusion: humans are more innovative, AI is more predictable, but together they enhance each other.
🔗 Details
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📂 Full description
In this comprehensive course, AI and LLM expert Sinan Ozdemir shares with you the knowledge and skills to assess LLM performance effectively. Get a detailed introduction to the process of evaluating LLMs, Multimodal AI, and AI-powered applications like agents and RAG. Learn how to thoroughly assess and evaluate these powerful and often unwieldy AI tools so you can make sure they meet your real-world needs. This course prepares you to evaluate and optimize LLMs so you can produce cutting edge AI applications.
This course was created by Pearson. We are pleased to host this training in our library.
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🔅 Complete Guide to Evaluating Large Language Models (LLMs)
🌐 Author: Sinan Ozdemir
🔰 Level: Intermediate
⏰ Duration: 7h 56m
🌀 Equip yourself with the knowledge and skills to assess LLM performance effectively.📗 Topics: Retrieval-Augmented Generation, Large Language Models, Artificial Intelligence 📤 Join Artificial intelligence for more courses
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🎓 Post-Degree Generation: AI is Changing the Hiring Game!
◽️ In the era of artificial intelligence, graduation degrees are losing their shine, especially for the class of 2025, where nearly half see the university degree as just an expensive souvenir from the pre-ChatGPT era.
🔹 Companies today don’t ask about honors or credit hours, but demand:
“Show me your skills in Prompt Engineering, not Latin!”
▪️ The resume reset button has been pressed, and the most important skill now is:
“Fluency in using AI”… or nothing!
♦️ Universities still grant degrees, but the market now rewards those who master the tools of the new reality.
In this age, those who don’t speak the language of algorithms… are completely out of the game.
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💥MassGen
🛠MassGen is a system for interaction between different AI agents, using collaborative artificial intelligence to solve complex tasks by distributing assignments among multiple agents.
🔰Key features include model synergy, parallel processing, knowledge sharing, consensus building, and live visualization, enabling agents to work effectively together and achieve the best results.
🔰The complex architecture of MassGen supports integration with three major model providers: Google Gemini, OpenAI, and xAI Grok, and also offers the ability to extend functionality with custom tools and an interactive mode for conducting dialogues.
🔗 Links: https://github.com/Leezekun/MassGen
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🚀 500+ AI Agents Projects — the largest collection of real projects with AI agents
Ashish Patel has compiled a collection of 500+ projects where AI agents are used in various fields — from medicine to finance and customer support.
🧠 What's inside:
— Open source cases: trading bots, assistants, recommendation systems
— Support for popular frameworks: CrewAI, AutoGen, LangGraph, and others
— Agent solutions for market analysis, resume generation, video assistants, lawyers, and even doctors
— Educational agents, recruiting, customer service, and legal-tech projects
— Links to repositories, task descriptions, and ideas for expansion
📌 Why this is useful:
✔️ A great start for your own project
✔️ Convenient to search by industry and technology
✔️ Lots of inspiration for hackathons, research, and automation
✔️ Community support: you can add your own cases
📌 Github
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🧠 10 Must-Have AI Tools in 2025!
◽️ Looking for tools that get tasks done quickly and deliver professional results? Here are the most powerful AI tools you must try this year, with hidden links for each tool:
🔹 Pictory.ai Tool
Automatically edit videos from texts or ready clips with cinematic quality, perfect for content creators and YouTubers.
🔹 ChatGPT Tool
Your smart assistant for problem-solving, content generation, programming, creative thinking, and everything you can imagine.
🔹 MidJourney Tool
An amazing artistic image generator using only text descriptions, with stunning resolution and realism.
🔹 Replit Tool
An interactive development environment that lets you write and run code, with AI support that suggests and corrects as you work.
🔹 Synthesia Tool
Create professional videos with virtual talking faces, used in training, marketing, and education.
🔹 Soundraw Tool
Generate original music tracks based on the type of content or desired mood, ideal for videos and podcasts.
🔹 Fliki Tool
Automatically convert texts into short videos, with voiceover and attractive visuals suitable for platforms like TikTok and Reels.
🔹 Starry Tool
Create avatars with high-quality artistic techniques, suitable for profiles, games, and marketing.
🔹 SlidesAI Tool
Turn any text into a professional PowerPoint slide deck in seconds, no manual design needed.
🔹 Remini Tool
Automatically enhance old or low-quality photos and restore details with ultra-high precision.
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From generating images and music to writing code and designing presentations… these tools are your magic toolkit in 2025!
