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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 94 001 suscriptores, ocupando la posición 1 568 en la categoría Educación y el puesto 3 028 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 94 001 suscriptores.
Según los últimos datos del 23 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 993, y en las últimas 24 horas de 92, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 7.92%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.62% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 7 435 visualizaciones. En el primer día suele acumular 1 526 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 24 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.
94 001
Suscriptores
+9224 horas
+1097 días
+99330 días
Archivo de publicaciones
94 001
🚀 TrajectoryCrafter (Moving-Camera Diffusion) is a new tool from Tencent that offers a new approach to redirecting camera trajectories in monochrome videos.
How the model works:
🌟 Initialization :
starts with an existing camera trajectory or even pure noise. This sets the initial state that the model will gradually improve.
The model uses two types of input data simultaneously: rendered point clouds (3D representations of scenes) and source videos.
🌟 Diffusion process:
The model learns to “clean up” random noise step by step, turning it into a sequence of trajectories. At each step, iterative refinement occurs — the model predicts what a more realistic trajectory should look like, based on given conditions (e.g., smoothness of motion, and consistency of the scene).
Instead of using only videos taken from different angles, the authors created a training set by combining extensive monocular videos (with a regular camera) with limited but high-quality multi-view videos. This strategy is achieved using what is called “double reprojection”, which helps the model better adapt to different scenes.
🌟 Generating the final trajectory:
After a series of iterations, when the noise is removed, a new camera trajectory is generated that meets the given conditions and has high quality visual dynamics.
Installation :
git clone --recursive https://github.com/TrajectoryCrafter/TrajectoryCrafter.git
cd TrajectoryCrafter
🖥 Github
🟡 Article
🟡 Project
🟡 Demo
🟡 Video94 001
🔅 AI Projects with Python, TensorFlow, and NLTK
📝 Supercharge your technical know-how and start building AI projects using Python, TensorFlow, and NLTK.
🌐 Author: Dhhyey Desai
🔰 Level: Intermediate
⏰ Duration: 24m
📋 Topics: TensorFlow, Artificial Intelligence, NLTK
🔗 Join Artificial intelligence for more courses
94 001
🔅 PREMIUM CHANNELS
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🔰 Web Development
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221k| 🔰 Linkedin Learning
139k| 🔰 Udemy Premium
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118k| 🔰 Python 3
100k| 🔰 JavaScript Training
089k| 🔰 Machine Learning
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068k| 🔰 Data Analysis and Databases
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062k| 🔰 Linux and DevOps
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048k| 🔰 OpenAI Mastery
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047k| 🔰 Business and Finance
045k| 🔰 Best Telegram Channels
041k| 🔰 Udemy Learning
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040k| 🔰 Zero to Mastery
040k| 🔰 Mobile Apps
036k| 🔰 Linkedin Learning Courses
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035k| 🔰 Codedamn Courses
034k| 🔰 React 101
031k| 🔰 Crypto Tutorials
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030k| 🔰 Coding Interview
025k| 🔰 Telegram's Shorts
022k| 🔰 Linux Training
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🔰 2hrs on top & 8hrs in channel!
94 001
📱Artificial intelligence
📱Advanced LLMs with Retrieval Augmented Generation (RAG): Practical Projects for AI Applications
94 001
🔅 Advanced LLMs with Retrieval Augmented Generation (RAG): Practical Projects for AI Applications
📝 Discover the core concepts of successful AI applications using LLMs to achieve high levels of performance and accuracy.
🌐 Author: Guy Ernest
🔰 Level: Advanced
⏰ Duration: 1h 47m
📋 Topics: Retrieval-Augmented Generation, Large Language Models, Artificial Intelligence
🔗 Join Artificial intelligence for more courses
94 001
💡 9 AI Skills to Master in 2026
It’s the infrastructure behind how smart businesses run today.
The gap between users and experts is closing fast.
But the gap between curiosity and capability is getting wider.
The difference comes down to skill, not just tools.
These are the nine that matter most in 2026.
Each one compounds the rest and turns AI from novelty into leverage.
1⃣ Prompt Engineering to ask better questions and get sharper answers
🔢 AI Workflow Automation to connect apps and remove repetitive work
🔢 AI Agents to build systems that act without human input
🔢 Retrieval-Augmented Generation (RAG) to give models access to your own data
🔢 Fine-Tuning and Custom GPTs to train models for your goals and tone
🔢 Multimodal AI to mix text, image, and audio in one workflow
🔢 AI Video Generation to turn ideas into content without editing tools
🔢 AI Tool Stacking to link platforms into a single automated system
🔢 LLM Evaluation and Management to measure accuracy, cost, and performance
94 001
🔅 PREMIUM CHANNELS
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 Web Development
-◦-◦--◦--◦-◦--◦--◦-◦--
221k| 🔰 Linkedin Learning
139k| 🔰 Udemy Premium
134k| 🔰 Web Development
-◦-◦--◦-
118k| 🔰 Python 3
100k| 🔰 JavaScript Training
089k| 🔰 Machine Learning
-◦-◦--◦-
068k| 🔰 Artificial Intelligence
068k| 🔰 Data Analysis and Databases
064k| 🔰 React and NextJs
-◦-◦--◦-
061k| 🔰 Linux and DevOps
049k| 🔰 100 Days of Python
048k| 🔰 OpenAI Mastery
-◦-◦--◦-
047k| 🔰 Business and Finance
045k| 🔰 Best Telegram Channels
040k| 🔰 Udemy Learning
-◦-◦--◦-
040k| 🔰 Zero to Mastery
040k| 🔰 Mobile Apps
035k| 🔰 Linkedin Learning Courses
-◦-◦--◦-
035k| 🔰 Codedamn Courses
034k| 🔰 React 101
031k| 🔰 Crypto Tutorials
-◦-◦--◦-
030k| 🔰 Coding Interview
025k| 🔰 Telegram's Shorts
022k| 🔰 Linux Training
-◦-◦--◦-
022k| 🔰 The Coding Space
-◦-◦--◦--◦-◦--◦--◦-◦--
🔰 Add Your Channel
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🔰 2hrs on top & 8hrs in channel!
94 001
🔅 Natural Language Processing (NLP) on Amazon Bedrock
📝 This course addresses natural language AI tasks using Bedrock's LLMs, Amazon Q capabilities, and SageMaker NLP models.
🌐 Author: Noah Gift
🔰 Level: Intermediate
⏰ Duration: 56m
📋 Topics: Amazon Bedrock, Large Language Models, Natural Language Processing
🔗 Join Artificial intelligence for more courses
94 001
💡 The AI Universe
This visual guide clearly illustrates the different layers and concepts within Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI.
94 001
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94 001
🔅 Everyday AI Concepts
📝 Learn key artificial intelligence concepts and discover how AI can benefit your team, organization, products, and services.
🌐 Author: Doug Rose
🔰 Level: General
⏰ Duration: 49m
📋 Topics: Artificial Intelligence for Business
🔗 Join Artificial intelligence for more courses
