Artificial Intelligence
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🔰 Machine Learning & Artificial Intelligence Free Resources 🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more For Promotions: @love_data
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Сеть:📈 Аналитический обзор Telegram-канала Artificial Intelligence
Канал Artificial Intelligence (@machinelearning_deeplearning) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 56 585 подписчиков, занимая 3 068 место в категории Образование и 5 980 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 56 585 подписчиков.
Согласно последним данным от 29 октября, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 460, а за последние 24 часа — 4, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 3.83%. В первые 24 часа после публикации контент обычно набирает 1.44% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 2 166 просмотров. В течение первых суток публикация набирает 815 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 12.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как learning, classification, layer, pattern, chatbot.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“🔰 Machine Learning & Artificial Intelligence Free Resources
🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more
For Promotions: @love_data”
Благодаря высокой частоте обновлений (последние данные получены 30 октября, 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
+424 часа
+747 дней
+46030 дней
Архив постов
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15+ Must Watch Movies for Programmers🧑💻🤖
1. The Matrix
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𝟱 𝗙𝗥𝗘𝗘 𝗧𝗲𝗰𝗵 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗙𝗿𝗼𝗺 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁, 𝗔𝗪𝗦, 𝗜𝗕𝗠, 𝗖𝗶𝘀𝗰𝗼, 𝗮𝗻𝗱 𝗦𝘁𝗮𝗻𝗳𝗼𝗿𝗱. 😍
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10 Real-World AI Use Cases You Should Know
✅ Healthcare Diagnosis – AI detects diseases like cancer from X-rays & MRIs faster than humans
✅ Fraud Detection in Finance – Banks use ML to catch unusual transactions in real-time
✅ AI in Education – Personalized learning paths, grading automation, and virtual tutors
✅ Self-Driving Cars – AI helps vehicles understand surroundings and make split-second decisions
✅ Customer Service Chatbots – 24/7 support powered by natural language understanding
✅ Recommendation Systems – Netflix, Amazon, Spotify know your taste better than you
✅ Agriculture AI – Drones and sensors optimize irrigation, crop monitoring, and yield prediction
✅ Cybersecurity – AI detects threats and anomalies before they escalate
✅ Retail & Inventory – AI forecasts demand and automates stock management
✅ Voice Assistants – Siri, Alexa, and Google Assistant getting smarter every day
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10 AI Tools Every Developer Should Try
✅ GitHub Copilot – Your AI coding buddy that completes code in real-time
✅ Codeium – A free AI autocomplete alternative to Copilot
✅ Amazon CodeWhisperer – AI suggestions optimized for AWS developers
✅ Cursor – An AI-first code editor built on VS Code
✅ Polycoder – Open-source AI that understands multiple programming languages
✅ Blackbox AI – Lets you copy code from videos, images & PDFs
✅ Mutable AI – Write, refactor, and document code with AI
✅ AskCodi – Natural language to code generation
✅ Kite – Autocompletion powered by machine learning
✅ Replit Ghostwriter – AI assistant inside your online IDE
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𝗟𝗲𝗮𝗿𝗻 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗳𝗼𝗿 𝗙𝗥𝗘𝗘 & 𝗘𝗹𝗲𝘃𝗮𝘁𝗲 𝗬𝗼𝘂𝗿 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 𝗚𝗮𝗺𝗲!😍
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10 New & Trending AI Concepts You Should Know in 2025
✅ Retrieval-Augmented Generation (RAG) – Combines search with generative AI for smarter answers
✅ Multi-Modal Models – AI that understands text, image, audio, and video (like GPT-4V, Gemini)
✅ Agents & AutoGPT – AI that can plan, execute, and make decisions with minimal input
✅ Synthetic Data Generation – Creating fake yet realistic data to train AI models
✅ Federated Learning – Train models without moving your data (privacy-first AI)
✅ Prompt Engineering – Crafting prompts to get the best out of LLMs
✅ Fine-Tuning & LoRA – Customize big models for specific tasks with minimal resources
✅ AI Safety & Alignment – Making sure AI systems behave ethically and predictably
✅ TinyML – Running ML models on edge devices with very low power (IoT focus)
✅ Open-Source LLMs – Rise of models like Mistral, LLaMA, Mixtral challenging closed-source giants
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𝟰 𝗙𝗥𝗘𝗘 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍
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10 Python Libraries Every AI Developer Should Know
✅ NumPy – Foundation for numerical computing in Python
✅ Pandas – Data manipulation and analysis made easy
✅ Scikit-learn – Powerful library for classical ML models
✅ TensorFlow – End-to-end open-source ML platform by Google
✅ PyTorch – Deep learning framework loved by researchers
✅ Matplotlib – Create stunning data visualizations
✅ Seaborn – High-level interface for drawing statistical plots
✅ NLTK – Toolkit for working with human language data (NLP)
✅ OpenCV – Real-time computer vision made simple
✅ Hugging Face Transformers – Pretrained models for NLP, CV, and more
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Python For Everything!🐍
Python, the versatile language, can be combined with various libraries to build amazing things:🚀
1. Python + Pandas = Data Manipulation
2. Python + Scikit-Learn = Machine Learning
3. Python + TensorFlow = Deep Learning
4. Python + Matplotlib = Data Visualization
5. Python + Seaborn = Advanced Visualization
6. Python + Flask = Web Development
7. Python + Pygame = Game Development
8. Python + Kivy = Mobile App Development
#Python
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𝗚𝗼𝗼𝗴𝗹𝗲 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍
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+1
Stanford’s Machine Learning - by Andrew Ng
A complete lecture notes of 227 pages. Available Free.
Download the notes:
cs229.stanford.edu/main_notes.pdf
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Repost from Data Science & Machine Learning
Hey folks! Just curious — where are you in your Data & AI journey?
