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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
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 94 001 подписчиков, занимая 1 568 место в категории Образование и 3 028 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 94 001 подписчиков.
Согласно последним данным от 23 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 993, а за последние 24 часа — 92, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 7.92%. В первые 24 часа после публикации контент обычно набирает 1.62% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 7 435 просмотров. В течение первых суток публикация набирает 1 526 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 9.
- 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 24 июня, 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.
94 001
Подписчики
+9224 часа
+1097 дней
+99330 день
Архив постов
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
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📱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
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221k| 🔰 Linkedin Learning
139k| 🔰 Udemy Premium
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118k| 🔰 Python 3
100k| 🔰 JavaScript Training
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068k| 🔰 Artificial Intelligence
068k| 🔰 Data Analysis and Databases
064k| 🔰 React and NextJs
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061k| 🔰 Linux and DevOps
049k| 🔰 100 Days of Python
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047k| 🔰 Business and Finance
045k| 🔰 Best Telegram Channels
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040k| 🔰 Zero to Mastery
040k| 🔰 Mobile Apps
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034k| 🔰 React 101
031k| 🔰 Crypto Tutorials
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025k| 🔰 Telegram's Shorts
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022k| 🔰 The Coding Space
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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
+1
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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
