¡Ya disponible! Investigación de Telegram 2025 — los principales insights del año 
AI and Machine Learning
Ir al canal en Telegram
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 94 192 suscriptores, ocupando la posición 1 545 en la categoría Educación y el puesto 3 012 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 94 192 suscriptores.
Según los últimos datos del 30 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 965, y en las últimas 24 horas de 57, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 7.33%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 2.71% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 6 902 visualizaciones. En el primer día suele acumular 2 549 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 9.
- 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 01 julio, 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.
94 192
Suscriptores
+5724 horas
+2587 días
+96530 días
Archivo de publicaciones
94 192
Found this - AI Builders, pay attention.
A curated marketplace just launched where AI builders list their systems and get paid - setup fee + monthly recurring. No sales, no client chasing. They handle everything, you just build.
100% free to join. No fees, no subscription, no hidden costs. They only take 20% when you earn - on setup fee and recurring. That's it.
Accepted builders are earning from day one. Spots are limited by design.
Takes 5 minutes to apply. You'll need a 90-second video of your system in action.
→ brainlancer.com
Daily updates from the CEO: https://www.linkedin.com/in/soner-catakli/
Follow, like & share in "your network" - these guys are building something seriously worth watching.
PS: First systems go live tomorrow. Builders who join early get the best positioning... investor-backed marketing means they bring the clients to you.
94 192
Found this - AI Builders, pay attention.
A curated marketplace just launched where AI builders list their systems and get paid - setup fee + monthly recurring. No sales, no client chasing. They handle everything, you just build.
100% free to join. No fees, no subscription, no hidden costs. They only take 20% when you earn - on setup fee and recurring. That's it.
Accepted builders are earning from day one. Spots are limited by design.
Takes 5 minutes to apply. You'll need a 90-second video of your system in action.
→ https://tglink.io/a774ad3a95379d
Daily updates from the CEO: https://tglink.io/2d46683619ea24
Follow, like & share in "your network" - these guys are building something seriously worth watching.
PS: First systems go live tomorrow. Builders who join early get the best positioning... investor-backed marketing means they bring the clients to you.
94 192
+1
Python Developer
Supervised learning is a type of machine learning where the model learns to map input data to output labels based on labeled training data.
The model is trained on a dataset that contains input-output pairs, and it learns the relationship between inputs and corresponding outputs.
The goal is for the model to generalize well to new, unseen data and accurately predict outputs for new inputs. Common supervised learning tasks include classification and regression.
94 192
🔅 PREMIUM CHANNELS
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 Web Development
-◦-◦--◦--◦-◦--◦--◦-◦--
217k| 🔰 Linkedin Learning
143k| 🔰 Udemy Premium
132k| 🔰 Web Development
-◦-◦--◦-
121k| 🔰 Python 3
097k| 🔰 JavaScript Training
091k| 🔰 Machine Learning
-◦-◦--◦-
070k| 🔰 Data Analysis and Databases
068k| 🔰 Artificial Intelligence
064k| 🔰 Linux and DevOps
-◦-◦--◦-
063k| 🔰 React and NextJs
050k| 🔰 100 Days of Python
049k| 🔰 OpenAI Mastery
-◦-◦--◦-
049k| 🔰 Business and Finance
043k| 🔰 Best Telegram Channels
042k| 🔰 Udemy Learning
-◦-◦--◦-
040k| 🔰 Zero to Mastery
040k| 🔰 Mobile Apps
036k| 🔰 Linkedin Learning Courses
-◦-◦--◦-
035k| 🔰 Codedamn Courses
034k| 🔰 React 101
031k| 🔰 Coding Interview
-◦-◦--◦-
030k| 🔰 Crypto Tutorials
025k| 🔰 Telegram's Shorts
024k| 🔰 The Coding Space
-◦-◦--◦-
023k| 🔰 Linux Training
-◦-◦--◦--◦-◦--◦--◦-◦--
🔰 Add Your Channel
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 2hrs on top & 8hrs in channel!
94 192
🔅 Deep Learning Fundamentals for Healthcare
📝 Learn about deep learning in healthcare with this comprehensive course, including fundamentals, practical applications, advanced techniques, and more.
🌐 Author: Wuraola Oyewusi
🔰 Level: Intermediate
⏰ Duration: 2h 26m
📋 Topics: Healthcare Information Technology, Deep Learning, Computer Vision
🔗 Join Artificial intelligence for more courses
94 192
📖We translate any PDF documents in one click
🛠 PDFMathTranslate is a free AI-powered tool for full-text translation of PDF documents.
🔰 Neural networks will translate books, articles, diagrams and graphs, preserving their presentable appearance
🔹 Works very quickly - even a 200-page article can be translated in a minute
🔹 Completely preserves the text layout and does not make phrases clumsy
🔹 Knows 10 languages
🔗Links:
https://github.com/Byaidu/PDFMathTranslate
94 192
🔅 PREMIUM CHANNELS
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 Web Development
-◦-◦--◦--◦-◦--◦--◦-◦--
217k| 🔰 Linkedin Learning
143k| 🔰 Udemy Premium
132k| 🔰 Web Development
-◦-◦--◦-
121k| 🔰 Python 3
097k| 🔰 JavaScript Training
091k| 🔰 Machine Learning
-◦-◦--◦-
070k| 🔰 Data Analysis and Databases
068k| 🔰 Artificial Intelligence
064k| 🔰 Linux and DevOps
-◦-◦--◦-
063k| 🔰 React and NextJs
049k| 🔰 100 Days of Python
049k| 🔰 OpenAI Mastery
-◦-◦--◦-
049k| 🔰 Business and Finance
043k| 🔰 Best Telegram Channels
042k| 🔰 Udemy Learning
-◦-◦--◦-
040k| 🔰 Zero to Mastery
040k| 🔰 Mobile Apps
036k| 🔰 Linkedin Learning Courses
-◦-◦--◦-
035k| 🔰 Codedamn Courses
034k| 🔰 React 101
031k| 🔰 Coding Interview
-◦-◦--◦-
030k| 🔰 Crypto Tutorials
025k| 🔰 Telegram's Shorts
024k| 🔰 The Coding Space
-◦-◦--◦-
023k| 🔰 Linux Training
-◦-◦--◦--◦-◦--◦--◦-◦--
🔰 Add Your Channel
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 2hrs on top & 8hrs in channel!
94 192
🤖Chat SDK
🛠 Chat SDK is a free, open-source template built with Next.js and the AI SDK that helps you quickly build powerful chatbot applications.
⚙️ Features
🔰Next.js App Router
🔹Advanced routing for seamless navigation and performance
🔹React Server Components (RSCs) and Server Actions for server-side rendering and increased performance
🔰AI SDK
🔹Unified API for generating text, structured objects, and tool calls with LLMs
🔹Hooks for building dynamic chat and generative user interfaces
🔹Supports xAI (default), OpenAI, Fireworks, and other model providers
🔰shadcn/ui
🔹Styling with Tailwind CSS
🔹Component primitives from
🔹Radix UI for accessibility and flexibility
🔰Data Persistence
🔹Neon Serverless Postgres for saving chat history and user data
🔹Vercel Blob for efficient file storage
🔰Auth.js
🔹Simple and secure authentication
🔗Links:
https://github.com/vercel/ai-chatbot
🌐Site:
https://chat.vercel.ai/
94 192
🔅 Deep Learning with Python: Optimizing Deep Learning Models
📝 Leverage techniques for optimizing deep learning models and implementing them using Python.
🌐 Author: Frederick Nwanganga
🔰 Level: Intermediate
⏰ Duration: 2h 1m
📋 Topics: Deep Learning, Python
🔗 Join Artificial intelligence for more courses
94 192
🧠 10 Machine Learning Concepts You Must Know
✅ Supervised vs Unsupervised Learning – Understand the foundation of ML tasks
✅ Bias-Variance Tradeoff – Balance underfitting and overfitting
✅ Feature Engineering – The secret sauce to boost model performance
✅ Train-Test Split & Cross-Validation – Evaluate models the right way
✅ Confusion Matrix – Measure model accuracy, precision, recall, and F1
✅ Gradient Descent – The algorithm behind learning in most models
✅ Regularization (L1/L2) – Prevent overfitting by penalizing complexity
✅ Decision Trees & Random Forests – Interpretable and powerful models
✅ Support Vector Machines – Great for classification with clear boundaries
✅ Neural Networks – The foundation of deep learning
