Machine Learning
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Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho
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Red:📈 Análisis del canal de Telegram Machine Learning
El canal Machine Learning (@machinelearning9) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 40 403 suscriptores, ocupando la posición 3 324 en la categoría Tecnologías y Aplicaciones y el puesto 225 en la región Siria.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 403 suscriptores.
Según los últimos datos del 13 julio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 421, y en las últimas 24 horas de 25, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.65%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.74% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 1 070 visualizaciones. En el primer día suele acumular 701 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 4.
- Intereses temáticos: El contenido se centra en temas clave como distance, insidead, gpu, learning, degree.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Real Machine Learning — simple, practical, and built on experience.
Learn step by step with clear explanations and working code.
Admin: @HusseinSheikho || @Hussein_Sheikho”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 14 julio, 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.
40 403
Suscriptores
+2524 horas
+1547 días
+42130 días
Archivo de publicaciones
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🔥 Trending Repository: CDP8
📝 Description: New version of CDP software
🔗 Repository URL: https://github.com/ComposersDesktop/CDP8
📖 Readme: https://github.com/ComposersDesktop/CDP8#readme
📊 Statistics:
🌟 Stars: 313 stars
👀 Watchers: 16
🍴 Forks: 19 forks
💻 Programming Languages: C
🏷️ Related Topics: Not available
==================================
🧠 By: https://t.me/DataScienceM
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🔥 Trending Repository: terminal-bench
📝 Description: A benchmark for LLMs on complicated tasks in the terminal
🔗 Repository URL: https://github.com/laude-institute/terminal-bench
🌐 Website: https://www.tbench.ai
📖 Readme: https://github.com/laude-institute/terminal-bench#readme
📊 Statistics:
🌟 Stars: 428 stars
👀 Watchers: 7
🍴 Forks: 130 forks
💻 Programming Languages: Python - JetBrains MPS - Shell - C++ - Dockerfile - C
🏷️ Related Topics: Not available
==================================
🧠 By: https://t.me/DataScienceM
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🔥 Trending Repository: self-hosted-ai-starter-kit
📝 Description: The Self-hosted AI Starter Kit is an open-source template that quickly sets up a local AI environment. Curated by n8n, it provides essential tools for creating secure, self-hosted AI workflows.
🔗 Repository URL: https://github.com/n8n-io/self-hosted-ai-starter-kit
🌐 Website: https://n8n.io
📖 Readme: https://github.com/n8n-io/self-hosted-ai-starter-kit#readme
📊 Statistics:
🌟 Stars: 11.5K stars
👀 Watchers: 153
🍴 Forks: 2.8K forks
💻 Programming Languages: Not available
🏷️ Related Topics:
#ai #self_hosted #starter_kit #low_code #ai_agents================================== 🧠 By: https://t.me/DataScienceM
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🔥 Trending Repository: leantime
📝 Description: Leantime is a goals focused project management system for non-project managers. Building with ADHD, Autism, and dyslexia in mind.
🔗 Repository URL: https://github.com/Leantime/leantime
🌐 Website: https://leantime.io
📖 Readme: https://github.com/Leantime/leantime#readme
📊 Statistics:
🌟 Stars: 5.8K stars
👀 Watchers: 69
🍴 Forks: 671 forks
💻 Programming Languages: PHP - JavaScript - CSS - Blade - Twig - HTML
🏷️ Related Topics:
#php #trello #jira #sql #agile #calendar #projects #project_management #kanban #scrum #lean #strategy #timesheets #asana #gantt #hacktoberfest #notion #retrospective #clickup #leantime================================== 🧠 By: https://t.me/DataScienceM
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🔥 Trending Repository: clients
📝 Description: Bitwarden client apps (web, browser extension, desktop, and cli).
🔗 Repository URL: https://github.com/bitwarden/clients
🌐 Website: https://bitwarden.com
📖 Readme: https://github.com/bitwarden/clients#readme
📊 Statistics:
🌟 Stars: 10.6K stars
👀 Watchers: 124
🍴 Forks: 1.4K forks
💻 Programming Languages: TypeScript - HTML - SCSS - Rust - MDX - JavaScript
🏷️ Related Topics:
#electron #nodejs #javascript #cli #firefox #chrome #angular #typescript #desktop #safari #webextension #browser_extension #bitwarden================================== 🧠 By: https://t.me/DataScienceM
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🔥 Trending Repository: puppeteer
📝 Description: JavaScript API for Chrome and Firefox
🔗 Repository URL: https://github.com/puppeteer/puppeteer
🌐 Website: https://pptr.dev
📖 Readme: https://github.com/puppeteer/puppeteer#readme
📊 Statistics:
🌟 Stars: 91.8K stars
👀 Watchers: 1.2k
🍴 Forks: 9.3K forks
💻 Programming Languages: TypeScript - JavaScript - HTML
🏷️ Related Topics:
#testing #firefox #chrome #automation #web #chromium #developer_tools #node_module #headless_chrome================================== 🧠 By: https://t.me/DataScienceM
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🔥 Trending Repository: airi
📝 Description: 💖🧸 Self hosted, you owned Grok Companion, a container of souls of waifu, cyber livings to bring them into our worlds, wishing to achieve Neuro-sama's altitude. Capable of realtime voice chat, Minecraft, Factorio playing. Web / macOS / Windows supported.
🔗 Repository URL: https://github.com/moeru-ai/airi
🌐 Website: https://airi.moeru.ai/docs/
📖 Readme: https://github.com/moeru-ai/airi#readme
📊 Statistics:
🌟 Stars: 3.1K stars
👀 Watchers: 14
🍴 Forks: 215 forks
💻 Programming Languages: Vue - TypeScript - Rust - C++ - HTML - CSS
🏷️ Related Topics:
#live2d #vrm #digital_life #vtuber #neurosama #ai_vtuber #neuro_sama #moeru_ai #ai_companion #grok_companion================================== 🧠 By: https://t.me/DataScienceM
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🔥 Trending Repository: sim
📝 Description: Sim is an open-source AI agent workflow builder. Sim Studio's interface is a lightweight, intuitive way to quickly build and deploy LLMs that connect with your favorite tools.
🔗 Repository URL: https://github.com/simstudioai/sim
🌐 Website: https://www.sim.ai
📖 Readme: https://github.com/simstudioai/sim#readme
📊 Statistics:
🌟 Stars: 7.7K stars
👀 Watchers: 56
🍴 Forks: 1K forks
💻 Programming Languages: TypeScript - MDX - Python - CSS - Shell - Smarty
🏷️ Related Topics:
#react #automation #typescript #ai #nextjs #chatbot #artificial_intelligence #gemini #openai #agents #low_code #no_code #rag #anthropic #deepseek #aiagents #agentic_workflow #agent_workflow================================== 🧠 By: https://t.me/DataScienceM
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✨ Sharpen Your Vision: Super-Resolution of CCTV Images Using Hugging Face Diffusers ✨
📖 Table of Contents Sharpen Your Vision: Super-Resolution of CCTV Images Using Hugging Face Diffusers Configuring Your Development Environment Problem Statement How Does Super-Resolution Solve This? State-of-the-Art Approaches Generative Adversarial Networks (GANs) Diffusion Models Implementing Diffus...
🏷️ #ArtificialIntelligence #ComputerVision #DeepLearning #ImageProcessing #MachineLearning #Tutorial
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✨ Face detection tips, suggestions, and best practices ✨
📖 In this tutorial, you will learn my tips, suggestions, and best practices to achieve high face detection accuracy with OpenCV and dlib. We’ve covered face detection four times on the PyImageSearch blog: Face detection with OpenCV and Haar cascades Face…...
🏷️ #FaceApplications #OpenCVTutorials #Tutorials
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✨ What is face recognition? ✨
📖 In this tutorial, you will learn about face recognition, including: How face recognition works How face recognition is different from face detection A history of face recognition algorithms State-of-the-art algorithms used for face recognition today Next week we will start…...
🏷️ #FaceApplications
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✨ Face Recognition with Local Binary Patterns (LBPs) and OpenCV ✨
📖 In this tutorial, you will learn how to perform face recognition using Local Binary Patterns (LBPs), OpenCV, and the cv2.face.LBPHFaceRecognizer_create function. In our previous tutorial, we discussed the fundamentals of face recognition, including: The difference between face detection and face…...
🏷️ #FaceApplications #OpenCVTutorials #Tutorials
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✨ OpenCV Eigenfaces for Face Recognition ✨
📖 In this tutorial, you will learn how to implement face recognition using the Eigenfaces algorithm, OpenCV, and scikit-learn. Our previous tutorial introduced the concept of face recognition — detecting the presence of a face in an image/video and then subsequently…...
🏷️ #FaceApplications #OpenCVTutorials #Tutorials
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✨ How to configure your NVIDIA Jetson Nano for Computer Vision and Deep Learning ✨
📖 In today’s tutorial, you will learn how to configure your NVIDIA Jetson Nano for Computer Vision and Deep Learning with TensorFlow, Keras, TensorRT, and OpenCV. Two weeks ago, we discussed how to use my pre-configured Nano .img file — today,…...
🏷️ #DeepLearning #EmbeddedIoTandComputerVision #IoT #Tutorials
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✨ An interview with Brandon Gilles, creator of the OpenCV AI Kit (OAK) ✨
📖 In this post, I interview Brandon Gilles, a longtime PyImageSearch reader, and creator of the OpenCV AI Kit (OAK), which is revolutionizing how we are performing embedded computer vision and deep learning. To celebrate the 20th anniversary of the OpenCV…...
🏷️ #DeepLearning #EmbeddedIoTandComputerVision #Interviews #OpenCVAIKit
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✨ An interview with Jagadish Mahendran, 1st place winner of the OpenCV Spatial AI Competition ✨
📖 In this post, I interview Jagadish Mahendran, senior Computer Vision/Artificial Intelligence (AI) engineer who recently won 1st place in the OpenCV Spatial AI Competition using the new OpenCV AI Kit (OAK). Jagadish’s winning project was a computer vision system for…...
🏷️ #EmbeddedIoTandComputerVision #Interviews #OpenCVAIKit
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✨ Introduction to OpenCV AI Kit (OAK) ✨
📖 Table of Contents Introduction to OpenCV AI Kit (OAK) Introduction OAK Hardware OAK-1 OAK-D Limitation OAK-FFC OAK USB Hardware Offerings OAK PoE Hardware Offerings OAK Developer Kit OAK Modules Comparison Applications on OAK Image Classifier On-Device Face Detection Face Mask…...
🏷️ #EmbeddedIoTandComputerVision #EmbeddedIoTComputerVision #OAK #Tutorials
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✨ Training a custom dlib shape predictor ✨
📖 In this tutorial, you will learn how to train your own custom dlib shape predictor. You’ll then learn how to take your trained dlib shape predictor and use it to predict landmarks on input images and real-time video streams. Today…...
🏷️ #dlib #FaceApplications #FacialLandmarks #ShapePredictors #Tutorials
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✨ Tuning dlib shape predictor hyperparameters to balance speed, accuracy, and model size ✨
📖 In this tutorial, you will learn how to optimally tune dlib’s shape predictor hyperparameters and options to obtain a shape predictor that balances speed, accuracy, and model size. Today is part two in our two-part series on training custom shape…...
🏷️ #dlib #FaceApplications #FacialLandmarks #ShapePredictors #Tutorials
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✨ Optimizing dlib shape predictor accuracy with find_min_global ✨
📖 In this tutorial you will learn how to use dlib’s find_min_global function to optimize the options and hyperparameters to dlib’s shape predictor, yielding a more accurate model. A few weeks ago I published a two-part series on using dlib to…...
🏷️ #dlib #FaceApplications #FacialLandmarks #ShapePredictors #Tutorials
