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Artificial Intelligence
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🔒 Welcome Artificial Intelligence Channel Buy ads: https://telega.io/c/Artificial_Intelligence_COM
Mostrar más📈 Análisis del canal de Telegram Artificial Intelligence
El canal Artificial Intelligence (@artificial_intelligence_com) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 70 419 suscriptores, ocupando la posición 1 849 en la categoría Tecnologías y Aplicaciones y el puesto 4 785 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 70 419 suscriptores.
Según los últimos datos del 13 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 1 217, y en las últimas 24 horas de 69, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 7.35%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 2.09% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 5 179 visualizaciones. En el primer día suele acumular 1 474 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 10.
- Intereses temáticos: El contenido se centra en temas clave como learning, linkedin, linux, udemy, 040k|.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“🔒 Welcome Artificial Intelligence Channel
Buy ads: https://telega.io/c/Artificial_Intelligence_COM”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 14 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 Tecnologías y Aplicaciones.
70 419
Suscriptores
+6924 horas
+2577 días
+1 21730 días
Archivo de publicaciones
70 430
👨🏻💻 One of the most popular GitHub repositories for "learning and using algorithms in Python" is The Algorithms - Python repo with 196K stars.
✏️ It has a lot of organized and categorized code that you can use to find, read, and run different algorithms. Everything you can think of is here; from simple algorithms like sorting to advanced algorithms for machine learning, artificial intelligence, neural networks, and more.
✅ Why should we use it?
🔢 For learning: If you're looking to learn algorithms in action, this is great.
🔢 For practice: You can take the codes, run them, and modify them to better understand.
🔢 For projects : You can even use the codes here in real-life or academic projects.
🔢 For interviews: If you're preparing for data science interviews, this is full of practical algorithms.
┌ 🏳️🌈 The Algorithms - Python
└ 🐱 GitHub-Repos
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🔅 PREMIUM CHANNELS
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🔰 The Coding Space
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217k| 🔰 Linkedin Learning Courses
129k| 🔰 Premium Udemy Courses
127k| 🔰 Web Development
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107k| 🔰 Learn Python
096k| 🔰 JavaScript Courses
077k| 🔰 Machine Learning
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065k| 🔰 DevOps Tutorials
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058k| 🔰 Data Analysis and Databases
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051k| 🔰 Linux and DevOps
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032k| 🔰 Linkedin Learning
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70 430
Machine Learning Algorithms every data scientist should know:
📌 Supervised Learning:
🔹 Regression
∟ Linear Regression
∟ Ridge & Lasso Regression
∟ Polynomial Regression
🔹 Classification
∟ Logistic Regression
∟ K-Nearest Neighbors (KNN)
∟ Decision Tree
∟ Random Forest
∟ Support Vector Machine (SVM)
∟ Naive Bayes
∟ Gradient Boosting (XGBoost, LightGBM, CatBoost)
📌 Unsupervised Learning:
🔹 Clustering
∟ K-Means
∟ Hierarchical Clustering
∟ DBSCAN
🔹 Dimensionality Reduction
∟ PCA (Principal Component Analysis)
∟ t-SNE
∟ LDA (Linear Discriminant Analysis)
📌 Reinforcement Learning (Basics):
∟ Q-Learning
∟ Deep Q Network (DQN)
📌 Ensemble Techniques:
∟ Bagging (Random Forest)
∟ Boosting (XGBoost, AdaBoost, Gradient Boosting)
∟ Stacking
Don’t forget to learn model evaluation metrics: accuracy, precision, recall, F1-score, AUC-ROC, confusion matrix, etc.
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📱Artificial Intelligence and Machine Learning
📱Machine Learning Fundamentals for Healthcare
70 430
📂 Full description
Theres an increased demand to integrate AI and machine learning workflows into many different business sectors. This is especially true in todays unique and constantly evolving global healthcare landscape.In this course, instructor Wuraola Oyewusi provides an overview of how AI and machine learning can optimize healthcare processes, data analysis, health outcomes, and more. Along the way, gather insights drawn from real-world examples to address complex privacy and ethical considerations in the industry. Wuraola also shows you how to utilize machine learning for tabular healthcare datasets using a Google Colab Notebook, including clinical records, classification, predictions, regression, clustering, and localization.
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🔅 Machine Learning Fundamentals for Healthcare
🌐 Author: Wuraola Oyewusi
🔰 Level: Beginner
⏰ Duration: 1h 36m
🌀 Get an introduction to the fundamentals of machine learning and AI in this course designed for healthcare professionals.📗 Topics: Healthcare Information Technology, Machine Learning 📤 Join Artificial Intelligence and Machine Learning for more courses
70 430
🔅 PREMIUM CHANNELS
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🔰 The Coding Space
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217k| 🔰 Linkedin Learning Courses
128k| 🔰 Premium Udemy Courses
127k| 🔰 Web Development
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106k| 🔰 Learn Python
095k| 🔰 JavaScript Courses
077k| 🔰 Machine Learning
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065k| 🔰 DevOps Tutorials
059k| 🔰 Learn React and NextJs
057k| 🔰 Data Analysis and Databases
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051k| 🔰 Linux and DevOps
044k| 🔰 100 Days of Python
043k| 🔰 Best Telegram Channels
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040k| 🔰 Business Training
040k| 🔰 ChatGPT Mastery
036k| 🔰 Mobile Development
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035k| 🔰 Zero to Mastery
034k| 🔰 Udemy Learning
032k| 🔰 Codedamn Courses
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032k| 🔰 Linkedin Learning
031k| 🔰 React 101
029k| 🔰 Crypto Lessons
-◦-◦--◦-
027k| 🔰 Coding Interview
023k| 🔰 Telegram's Shorts
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🔰 Add Your Channel
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🔰 2hrs on top & 8hrs in channel!
70 430
🔅 PREMIUM CHANNELS
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 The Coding Space
-◦-◦--◦--◦-◦--◦--◦-◦--
217k| 🔰 Linkedin Learning Courses
128k| 🔰 Premium Udemy Courses
127k| 🔰 Web Development
-◦-◦--◦-
106k| 🔰 Learn Python
095k| 🔰 JavaScript Courses
077k| 🔰 Machine Learning
-◦-◦--◦-
065k| 🔰 DevOps Tutorials
059k| 🔰 Learn React and NextJs
057k| 🔰 Data Analysis and Databases
-◦-◦--◦-
051k| 🔰 Linux and DevOps
044k| 🔰 100 Days of Python
043k| 🔰 Best Telegram Channels
-◦-◦--◦-
040k| 🔰 Business Training
040k| 🔰 ChatGPT Mastery
036k| 🔰 Mobile Development
-◦-◦--◦-
035k| 🔰 Zero to Mastery
034k| 🔰 Udemy Learning
032k| 🔰 Codedamn Courses
-◦-◦--◦-
031k| 🔰 Linkedin Learning
031k| 🔰 React 101
029k| 🔰 Crypto Lessons
-◦-◦--◦-
026k| 🔰 Coding Interview
023k| 🔰 Telegram's Shorts
-◦-◦--◦--◦-◦--◦--◦-◦--
🔰 Add Your Channel
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🔰 2hrs on top & 8hrs in channel!
70 430
🔅 PREMIUM CHANNELS
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 The Coding Space
-◦-◦--◦--◦-◦--◦--◦-◦--
217k| 🔰 Linkedin Learning Courses
128k| 🔰 Premium Udemy Courses
127k| 🔰 Web Development
-◦-◦--◦-
106k| 🔰 Learn Python
095k| 🔰 JavaScript Courses
076k| 🔰 Machine Learning
-◦-◦--◦-
065k| 🔰 DevOps Tutorials
059k| 🔰 Learn React and NextJs
057k| 🔰 Data Analysis and Databases
-◦-◦--◦-
050k| 🔰 Linux and DevOps
044k| 🔰 100 Days of Python
043k| 🔰 Best Telegram Channels
-◦-◦--◦-
040k| 🔰 Business Training
040k| 🔰 ChatGPT Mastery
036k| 🔰 Mobile Development
-◦-◦--◦-
035k| 🔰 Zero to Mastery
034k| 🔰 Udemy Learning
032k| 🔰 Codedamn Courses
-◦-◦--◦-
031k| 🔰 Linkedin Learning
031k| 🔰 React 101
029k| 🔰 Crypto Lessons
-◦-◦--◦-
026k| 🔰 Coding Interview
023k| 🔰 Telegram's Shorts
-◦-◦--◦--◦-◦--◦--◦-◦--
🔰 Add Your Channel
-◦-◦--◦--◦-◦--◦--◦-◦--◦--◦-◦--◦-
🔰 2hrs on top & 8hrs in channel!
