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AI and Machine Learning

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

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📈 Аналітичний огляд Telegram-каналу AI and Machine Learning

Канал AI and Machine Learning (@machine_learning_courses) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 94 048 підписників, посідаючи 1 561 місце в категорії Освіта та 3 020 місце у регіоні Індія.

📊 Показники аудиторії та динаміка

З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 94 048 підписників.

За останніми даними від 24 червня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 986, а за останні 24 години на 67, загальне охоплення залишається високим.

  • Статус верифікації: Не верифікований
  • Рівень залученості (ER): Середній показник залученості аудиторії становить 6.50%. Протягом перших 24 годин після публікації контент зазвичай збирає 1.56% реакцій від загальної кількості підписників.
  • Охоплення публікацій: В середньому кожен допис отримує 6 109 переглядів. Протягом першої доби публікація в середньому набирає 1 470 переглядів.
  • Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 8.
  • Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як learning, llm, linkedin, linux, udemy.

📝 Опис та контентна політика

Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more! Buy ads: https://telega.io/c/machine_learning_courses

Завдяки високій частоті оновлень (останні дані отримано 25 червня, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Освіта.

94 048
Підписники
+6724 години
+1517 днів
+98630 день
Архів дописів
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🔗 Top 5 machine learning projects: 1. Predicting House Prices: Build a machine learning model that predicts house prices bas
🔗 Top 5 machine learning projects: 1. Predicting House Prices: Build a machine learning model that predicts house prices based on features such as location, size, number of bedrooms, etc. This project will help you understand regression techniques and feature engineering. 2. Image Classification: Create a model that can classify images into different categories such as cats vs. dogs, fruits, or handwritten digits. This project will introduce you to convolutional neural networks (CNNs) and image processing. 3. Sentiment Analysis: Develop a sentiment analysis model that can classify text data as positive, negative, or neutral. This project will help you learn natural language processing techniques and text classification algorithms. 4. Credit Card Fraud Detection: Build a model that can detect fraudulent credit card transactions based on transaction data. This project will help you understand anomaly detection techniques and imbalanced classification problems. 5. Recommendation System: Create a recommendation system that suggests products or movies to users based on their preferences and behavior. This project will introduce you to collaborative filtering and recommendation algorithms.

The Singularity is near—our world will soon change forever! Are you ready? Read the Manifesto now and secure your place in th
The Singularity is near—our world will soon change forever! Are you ready? Read the Manifesto now and secure your place in the future: https://aism.faith Subscribe to the channel: https://t.me/aism

🔗 Instill Core is a universal tool for working with unstructured data. This open-source project offers a comprehensive solut
🔗 Instill Core is a universal tool for working with unstructured data. This open-source project offers a comprehensive solution for ETL processing, data preparation for AI, and deployment of LLM models. The platform combines document, image, and video processing into a single workflow, which is especially valuable for RAG scenarios and building AI pipelines. Instill Core can be easily integrated into existing systems via the Python/TypeScript SDK or CLI. Local execution is possible via Docker, and ready-made recipes allow you to quickly deploy PDF parsing, web scraping, or image segmentation. 🔗 GitHub

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Machine Learning Roadmap 👆
Machine Learning Roadmap 👆

🌐 Web Development Resources – Learn & Build! 🔰 Welcome to the world of HTML, CSS, JavaScript, and modern frameworks. We sha
🌐 Web Development Resources – Learn & Build! 🔰 Welcome to the world of HTML, CSS, JavaScript, and modern frameworks.
We share practical tips, code snippets, tools, and real-world projects to help you grow as a developer — whether you're just starting out or looking to level up.
📖 Frontend & Backend 📁 Projects & GitHub Gems ⚡️ Productivity Boosts 📚 Learning Resources 🔗 Join the community and build something awesome every day!

📦 Exercise Files

📱Artificial intelligence 📱Hands-On PyTorch Machine Learning

📂 Full description Many of the worlds most exciting and innovative new tech projects leverage the power of machine learning. But if you want to set yourself apart as a data scientist or machine learning engineer, you need to stay up to date with the current tools and best practices for creating effective, predictable models.In this course, instructor Helen Sun shows you how to get up and running with PyTorch, the open-source machine learning framework known for its simplicity, performance, and APIs. Explore the basic concepts of PyTorch, including tensors, operators, and conversion to and from NumPy, as well as how to utilize autograd, which tracks the history of every computation recorded by the framework. By the end of this course, youll also be equipped with a new set of skills to get the most out of Torchvision, Torchaudio, and Torchtext.

🔅 Hands-On PyTorch Machine Learning 🌐 Author: Helen Sun 🔰 Level: Intermediate ⏰ Duration: 56m 🌀 Discover the fundamentals
🔅 Hands-On PyTorch Machine Learning 🌐 Author: Helen Sun 🔰 Level: IntermediateDuration: 56m
🌀 Discover the fundamentals of creating machine learning models with PyTorch, the open-source machine learning framework.
📗 Topics: PyTorch, Machine Learning 📤 Join Artificial intelligence for more courses

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🔗 5 Trending AI Jobs You Can’t Miss in 2025! 🤖 💻 Machine Learning Engineer 👉🏻 Average Salary: $114,000 👉🏻 What They Do
🔗 5 Trending AI Jobs You Can’t Miss in 2025! 🤖 💻 Machine Learning Engineer 👉🏻 Average Salary: $114,000 👉🏻 What They Do: Design and implement ML algorithms while collaborating with data scientists and engineers. 📊 📊 Data Scientist 👉🏻 Average Salary: $120,000 👉🏻 What They Do: Analyze data, build predictive models, and drive data-backed decisions. 📈 🔬 AI Research Scientist 👉🏻 Average Salary: $126,000 👉🏻 What They Do: Explore the future of AI by testing algorithms and driving innovation. 🌟 🤝 AI Ethic 👉🏻 Average Salary: $135,000 👉🏻 What They Do: Promote ethical AI development, address biases, and ensure fairness. 🌐 📈 AI Product Manager 👉🏻 Average Salary: $140,000 👉🏻 What They Do: Manage AI products for success, focusing on innovation and ethical impact. 🛠

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🔗 ML Libraries
🔗 ML Libraries

AvatarTalk Telegram Bot Train Soft Skills with AI-Powered Avatars
AvatarTalk Telegram Bot Train Soft Skills with AI-Powered Avatars

AvatarTalk Telegram Bot Train Soft Skills with AI-Powered Avatars
AvatarTalk Telegram Bot Train Soft Skills with AI-Powered Avatars

🔗 AI Agents for Beginners - A Course This course has 10 lessons covering the fundamentals of building AI Agents. 🔰Each less
🔗 AI Agents for Beginners - A Course
This course has 10 lessons covering the fundamentals of building AI Agents.
🔰Each lesson covers its own topic so start wherever you like! 🔰There is multi-language support for this course. 🔗 Links: https://github.com/microsoft/ai-agents-for-beginners