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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 94 048 подписчиков, занимая 1 561 место в категории Образование и 3 020 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 94 048 подписчиков.
Согласно последним данным от 24 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 986, а за последние 24 часа — 67, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 6.50%. В первые 24 часа после публикации контент обычно набирает 1.56% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 6 109 просмотров. В течение первых суток публикация набирает 1 470 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 8.
- 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 25 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.
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Подписчики
+6724 часа
+1517 дней
+98630 день
Архив постов
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🔗 Creating Your AI For Business Roadmap: A Step-by-Step Guide
Identify Business Objectives: Understand how AI can help achieve your goals, whether it's through automation, predictive analytics, AI chatbots, or innovative product development.
Evaluate Data Infrastructure: AI needs quality data. Assess your data collection, storage, and cleanliness to ensure your AI initiatives can thrive.
Assemble a Skilled Team: Combine business insight, technical skills, and data science. Include business strategists, AI specialists, and IT professionals, or seek external expertise as necessary.
Choose Appropriate AI Technology: Select AI tools like ML, NLP, RPA, or Computer Vision, aligned with your business needs.
Prototype Development: Start small with a pilot project to address specific challenges, refining AI models based on performance.
Scale and Optimize: Expand successful prototypes, integrating them into broader business operations and continuously optimizing.
Implement Change Management: Develop strategies to assist your workforce in adapting to AI, including training and understanding AI benefits.
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📂 Full description
It seems like new artificial intelligence tools are arriving every day, and even if youre interested in using AI in your work, figuring out where to start may seem like an overwhelming undertaking. In this course, Drew Falkman shows designers the ways that AI can help you to build designs faster, make your designs smarter and better, and even improve your dev handoff. Drew surveys the current tools like Figma, Magician, and Sprout, and details their strengths and weaknesses. He also looks at some full-featured design suites that can help you get to prototypes quickly, like Wondershare Mockitt, Visily, and Uizard. He explains how you can use these tools to go from paper sketch or screenshot to wireframe in seconds, or use a prompt to generate an entire prototype. Finally, he shows you how you can use AI to automate the process of turning your designs into code.
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🔅 Design to Code: Using AI to Build Faster
🌐 Author: Drew Falkman
🔰 Level: Intermediate
⏰ Duration: 1h 21m
🌀 Learn about the artificial intelligence tools that can improve and speed up your design process.📗 Topics: Artificial Intelligence for Design, Software Development, Artificial Intelligence 📤 Join Artificial intelligence for more courses
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🔅 PREMIUM CHANNELS
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🔰 The Coding Space
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042k| 🔰 Business Training
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036k| 🔰 Zero to Mastery
035k| 🔰 Udemy Learning
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032k| 🔰 Linkedin Learning
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030k| 🔰 Crypto Lessons
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027k| 🔰 Coding Interview
023k| 🔰 Telegram's Shorts
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🔰 2hrs on top & 8hrs in channel!
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How do you plan your events?
Now you can schedule and share meetings directly in Telegram — with the new app tCalendar.
Whether it’s work or organising your social life — tCalendar keeps everything in one smart, flexible space.
🗓️ Feed — All your events in one clean timeline. Just send an invite in chat or add people directly to the event.
👥Stacks — shared calendars for groups. Create a Stack to organise events in one place and invite others to join.
📅 Slots — your personal booking link. Let people book time with you — for meetings, services, or casual catch-ups.
✨ AI — send a message to the bot, and AI will automatically organize an event for you.
Try tCalendar now — it’s free! 👌
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🔗 What is an AI Agent?
An AI agent is a software program that can interact with its environment, gather data, and use that data to achieve predetermined goals. AI agents can choose the best actions to perform to meet those goals.Key characteristics of AI agents are as follows: An agent can perform autonomous actions without constant human intervention. Also, they can have a human in the loop to maintain control. - Agents have a memory to store individual preferences and allow for personalization. It can also store knowledge. An LLM can undertake information processing and decision-making functions. - Agents must be able to perceive and process the information available from their environment. - Agents can also use tools such as accessing the internet, using code interpreters and making API calls. - Agents can also collaborate with other agents or humans.
Multiple types of AI agents are available such as learning agents, simple reflex agents, model-based reflex agents, goal-based agents, and utility-based agents.A system with AI agents can be built with different architectural approaches. 1 - Single Agent: Agents can serve as personal assistants. 2 - Multi-Agent: Agents can interact with each other in collaborative or competitive ways. 3 - Human Machine: Agents can interact with humans to execute tasks more efficiently.
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📚 Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
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Intent | AI-Enhanced Telegram
🚨 Breaking: Telegram’s translator is off-air!
🌐 Intent’s rock-solid translation—86 languages in real time
⬆️ Chat swipe summons AI for seamless context replies
🎤 AI voice-to-text, lightning fast
🤖 One-click hub for GPT-4o, Claude 3.7, Gemini 2 & more
🎁 Limited-time free AI credits
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🟣 Confused by your lab test results? You’re not alone — but now, there’s a smarter way to take charge of your health.
✨ Meet @LabsHouseAiBot – your personal AI assistant for clear, reliable explanations of your blood tests.
🟣 Just enter your results, and in minutes you’ll get easy-to-understand insights on key markers like cholesterol, glucose, and more.
💡 Way better than basic ChatGPT — it’s built specifically for the interpretation of your medical results!
👉 Try it now: @LabsHouseAiBot — your health transformation starts today! 🚀
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🔅 PREMIUM CHANNELS
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 The Coding Space
-◦-◦--◦--◦-◦--◦--◦-◦--
217k| 🔰 Linkedin Learning Courses
129k| 🔰 Premium Udemy Courses
128k| 🔰 Web Development
-◦-◦--◦-
108k| 🔰 Learn Python
096k| 🔰 JavaScript Courses
078k| 🔰 Machine Learning
-◦-◦--◦-
064k| 🔰 DevOps Tutorials
060k| 🔰 Learn React and NextJs
059k| 🔰 Data Analysis and Databases
-◦-◦--◦-
052k| 🔰 Linux and DevOps
045k| 🔰 100 Days of Python
043k| 🔰 Best Telegram Channels
-◦-◦--◦-
041k| 🔰 Business Training
041k| 🔰 ChatGPT Mastery
036k| 🔰 Mobile Development
-◦-◦--◦-
036k| 🔰 Zero to Mastery
035k| 🔰 Udemy Learning
033k| 🔰 Codedamn Courses
-◦-◦--◦-
032k| 🔰 Linkedin Learning
031k| 🔰 React 101
030k| 🔰 Crypto Lessons
-◦-◦--◦-
027k| 🔰 Coding Interview
023k| 🔰 Telegram's Shorts
-◦-◦--◦--◦-◦--◦--◦-◦--
🔰 Add Your Channel
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 2hrs on top & 8hrs in channel!
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Call for papers on AI to AI Journey* conference journal has started!
Prize for the best scientific paper - over $12'000!
Selected papers will be published in the scientific journal Doklady Mathematics.
📖 The journal:
- Indexed in the largest bibliographic databases of scientific citations
- Accessible to an international audience and published in the world’s digital libraries.
Submit your article by August 20 and get the opportunity not only to publish your research the scientific journal, but also to present it at the AI Journey conference.
More detailed information can be found in the Selection Rules -> AI Journey
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+7
🔗 Most ML roadmaps
If you’re tired of bloated diagrams and endless theory, this one’s for you.This is the 10-step roadmap I wish someone gave me earlier focused on real-world impact, not just flashy model builds. Swipe through to see: ✅ The core skills you actually need ✅ What separates you from junior talent ✅ What most self-taught engineers skip Whether you’re transitioning from data analyst, coming from software dev, or just trying to stop tutorial-hopping...
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