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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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📈 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 40 398 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 40 398 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.

40 398
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Archivo de publicaciones
🔥 $10.000 WITH LISA! Lisa earned $200,000 in a month, and now it’s YOUR TURN! She’s made trading SO SIMPLE that anyone can d
🔥 $10.000 WITH LISA! Lisa earned $200,000 in a month, and now it’s YOUR TURN! She’s made trading SO SIMPLE that anyone can do it. ❗️Just copy her signals every day ❗️Follow her trades step by step ❗️Earn $1,000+ in your first week – GUARANTEED! 🚨 BONUS: Lisa is giving away $10,000 to her subscribers! Don’t miss this once-in-a-lifetime opportunity. Free access for the first 500 people only! 👉 CLICK HERE TO JOIN NOW 👈

✨ Detecting COVID-19 in X-ray images with Keras, TensorFlow, and Deep Learning ✨ 📖 In this tutorial, you will learn how to a
✨ Detecting COVID-19 in X-ray images with Keras, TensorFlow, and Deep Learning ✨ 📖 In this tutorial, you will learn how to automatically detect COVID-19 in a hand-created X-ray image dataset using Keras, TensorFlow, and Deep Learning. Like most people in the world right now, I’m genuinely concerned about COVID-19. I find myself constantly…... 🏷️ #DeepLearning #KerasandTensorFlow #MedicalComputerVision #Tutorials

✨ COVID-19: Face Mask Detector with OpenCV, Keras/TensorFlow, and Deep Learning ✨ 📖 In this tutorial, you will learn how to
✨ COVID-19: Face Mask Detector with OpenCV, Keras/TensorFlow, and Deep Learning ✨ 📖 In this tutorial, you will learn how to train a COVID-19 face mask detector on a custom dataset with OpenCV, Keras/TensorFlow, and Deep Learning. Last month, I authored a blog post on detecting COVID-19 in X-ray images using deep learning.…... 🏷️ #DeepLearning #FaceApplications #KerasandTensorFlow #MedicalComputerVision #ObjectDetection #Tutorials

✨ OpenCV Social Distancing Detector ✨ 📖 In this tutorial, you will learn how to implement a COVID-19 social distancing detec
✨ OpenCV Social Distancing Detector ✨ 📖 In this tutorial, you will learn how to implement a COVID-19 social distancing detector using OpenCV, Deep Learning, and Computer Vision. Today’s tutorial is inspired by PyImageSearch reader Min-Jun, who emailed in asking: Hi Adrian, I’ve seen a number of…... 🏷️ #DeepLearning #MedicalComputerVision #ObjectDetection #Tutorials

✨ Implementing Approximate Nearest Neighbor Search with KD-Trees ✨ 📖 Table of Contents Implementing Approximate Nearest Neig
✨ Implementing Approximate Nearest Neighbor Search with KD-Trees ✨ 📖 Table of Contents Implementing Approximate Nearest Neighbor Search with KD-Trees Introduction to Approximate Nearest Neighbor Search Mathematical Foundation KD-Trees for Approximate Nearest Neighbor Search Construction of KD-Trees Querying with KD-Trees Step 1: Forward Traversal Step 2: Computing th... 🏷️ #ApproximateNearestNeighbor #KDTree #MachineLearning #NearestNeighborAlgorithm #Tutorial

✨ Introduction to Gradio for Building Interactive Applications ✨ 📖 Table of Contents Introduction to Gradio for Building Int
✨ Introduction to Gradio for Building Interactive Applications ✨ 📖 Table of Contents Introduction to Gradio for Building Interactive Applications What Is Gradio? High-Impact Projects Powered by Gradio AUTOMATIC1111’s Stable Diffusion Web UI oobabooga’s Text Generation Web UI The Next Generation of Gradio: What’s New in Version 5 Performance Improvements…... 🏷️ #Gradio #MachineLearning #Python #SoftwareDevelopment #Tutorial

✨ FastAPI Meets OpenAI CLIP: Build and Deploy with Docker ✨ 📖 Table of Contents FastAPI Meets OpenAI CLIP: Build and Deploy
✨ FastAPI Meets OpenAI CLIP: Build and Deploy with Docker ✨ 📖 Table of Contents FastAPI Meets OpenAI CLIP: Build and Deploy with Docker Building on FastAPI Foundations What’s Next? What Is OpenAI CLIP? How OpenAI CLIP Works: Understanding Text-Image Matching and Contrastive Learning Contrastive Pre-Training: Aligning Text and Image Embeddings Shared…... 🏷️ #AIApplications #DockerDeployment #FastAPIDevelopment #MachineLearning #Tutorial

✨ Build a Search Engine: Deploy Models and Index Data in AWS OpenSearch ✨ 📖 Table of Contents Build a Search Engine: Deploy
✨ Build a Search Engine: Deploy Models and Index Data in AWS OpenSearch ✨ 📖 Table of Contents Build a Search Engine: Deploy Models and Index Data in AWS OpenSearch Introduction What Will We Do in This Blog? Why Are We Using Vector Embeddings? What’s Coming Next? Configuring Your Development Environment Installing Docker (Required for…... 🏷️ #Docker #MachineLearning #OpenSearch #SearchEngines #SemanticSearch #Tutorial #VectorSearch

✨ Data augmentation with tf.data and TensorFlow ✨ 📖 In this tutorial, you will learn two methods to incorporate data augment
✨ Data augmentation with tf.data and TensorFlow ✨ 📖 In this tutorial, you will learn two methods to incorporate data augmentation into your tf.data pipeline using Keras and TensorFlow. A good dataset of images is vital when working with data augmentation in TensorFlow. It enables us to see how…... 🏷️ #DeepLearning #KerasandTensorFlow #Tutorials

✨ Smile detection with OpenCV, Keras, and TensorFlow ✨ 📖 In this tutorial, we will be building a complete end-to-end applica
✨ Smile detection with OpenCV, Keras, and TensorFlow ✨ 📖 In this tutorial, we will be building a complete end-to-end application that can detect smiles in a video stream in real-time using deep learning along with traditional computer vision techniques. To accomplish this task, we’ll be training the LetNet architecture…... 🏷️ #DeepLearning #KerasandTensorFlow #Tutorials

✨ Breaking captchas with deep learning, Keras, and TensorFlow ✨ 📖 In the past, we’ve worked with datasets that have been pre
✨ Breaking captchas with deep learning, Keras, and TensorFlow ✨ 📖 In the past, we’ve worked with datasets that have been pre-compiled and labeled for us — but what if we wanted to go about creating our own custom dataset and then training a CNN on it? In this tutorial, I’ll…... 🏷️ #DeepLearning #KerasandTensorFlow #Tutorials

✨ CycleGAN: Unpaired Image-to-Image Translation (Part 1) ✨ 📖 Table of Contents CycleGAN: Unpaired Image-to-Image Translation
✨ CycleGAN: Unpaired Image-to-Image Translation (Part 1) ✨ 📖 Table of Contents CycleGAN: Unpaired Image-to-Image Translation (Part 1) Introduction Unpaired Image Translation CycleGAN Pipeline and Training Loss Formulation Adversarial Loss Cycle Consistency Summary Citation Information CycleGAN: Unpaired Image-to-Image Translation (Part 1) In this tutorial, yo... 🏷️ #ComputerVision #CycleGAN #DeepLearning #Keras #KerasandTensorFlow #TensorFlow #UnpairedImageTranslation

✨ An interview with Askat Kuzdeuov, computer vision and deep learning researcher ✨ 📖 In this blog post, I interview Askat Ku
✨ An interview with Askat Kuzdeuov, computer vision and deep learning researcher ✨ 📖 In this blog post, I interview Askat Kuzdeuov, a computer vision and deep learning researcher at the Institute of Smart Systems and Artificial Intelligence (ISSAI). Askat is not only a stellar researcher, but he’s an avid PyImageSearch reader as well.…... 🏷️ #DeepLearning #GenerativeAdversarialNetworksGANs #Interviews #SensorFusion

✨ An interview with Raul Garcia-Martin, PhD candidate and computer vision entrepreneur ✨ 📖 In this blog post, I sit down wit
✨ An interview with Raul Garcia-Martin, PhD candidate and computer vision entrepreneur ✨ 📖 In this blog post, I sit down with Raul Garcia-Martin, a PhD candidate in Biometric Recognition at the University Carlos III of Madrid. Raul’s work focuses on identifying individual people by their biometrics. You’re likely already familiar with the most…... 🏷️ #DeepLearning #Interviews #SensorFusion

✨ An interview with David Bonn, computer vision and wildfire detection expert ✨ 📖 Imagine this: You’ve built a brand new hom
✨ An interview with David Bonn, computer vision and wildfire detection expert ✨ 📖 Imagine this: You’ve built a brand new home out in the country, far from major cities. You need a break from all the hustle and bustle, and you want to bring yourself back to nature. The house you’ve built is…... 🏷️ #DeepLearning #EmbeddedIoTComputerVision #Interviews

✨ An Interview with Peter Ip, Chief Data Scientist ✨ 📖 Hey everyone, welcome to another blog post where we talk with student
✨ An Interview with Peter Ip, Chief Data Scientist ✨ 📖 Hey everyone, welcome to another blog post where we talk with students from PyImageSearch. Today we are joined by Peter Ip, a Chief Data Scientist. Ritwik: So Peter, maybe you could start by introducing yourself? What do you do, where…... 🏷️ #ChiefDataScientist #DeepLearning #Interviews

✨ Adversarial Learning with Keras and TensorFlow (Part 3): Exploring Adversarial Attacks Using Neural Structured Learning (NS
✨ Adversarial Learning with Keras and TensorFlow (Part 3): Exploring Adversarial Attacks Using Neural Structured Learning (NSL) ✨ 📖 Table of Contents Adversarial Learning with Keras and TensorFlow (Part 3): Exploring Adversarial Attacks Using Neural Structured Learning (NSL) Introduction to Advanced Adversarial Techniques in Machine Learning Harnessing NSL for Robust Model Training: Insights from Part 2 Deep Dive into…... 🏷️ #AdversarialLearning #DeepLearning #ImageProcessing #Keras #MachineLearning #NeuralNetworks #NeuralStructuredLearning #TensorFlow #Tutorial

✨ Unlocking Image Clarity: A Comprehensive Guide to Super-Resolution Techniques ✨ 📖 Table of Contents Unlocking Image Clarit
✨ Unlocking Image Clarity: A Comprehensive Guide to Super-Resolution Techniques ✨ 📖 Table of Contents Unlocking Image Clarity: A Comprehensive Guide to Super-Resolution Techniques Introduction Configuring Your Development Environment Need Help Configuring Your Development Environment? What Is Super-Resolution? Usual Problems with Low-Resolution Imagery Traditional Computer Vision A... 🏷️ #ArtificialIntelligence #ComputerVision #DeepLearning #ImageProcessing #MachineLearning #TechnologyApplications #Tutorial

🔥 Trending Repository: BitNet 📝 Description: Official inference framework for 1-bit LLMs 🔗 Repository URL: https://github.
🔥 Trending Repository: BitNet 📝 Description: Official inference framework for 1-bit LLMs 🔗 Repository URL: https://github.com/microsoft/BitNet 📖 Readme: https://github.com/microsoft/BitNet#readme 📊 Statistics: 🌟 Stars: 20.8K stars 👀 Watchers: 193 🍴 Forks: 1.6K forks 💻 Programming Languages: Python - C++ 🏷️ Related Topics: Not available ================================== 🧠 By: https://t.me/DataScienceM

🔥 Trending Repository: epicenter 📝 Description: Press shortcut → speak → get text. Free and open source. More local-first apps soon ❤️ 🔗 Repository URL: https://github.com/epicenter-so/epicenter 🌐 Website: https://epicenter.so/ 📖 Readme: https://github.com/epicenter-so/epicenter#readme 📊 Statistics: 🌟 Stars: 2.2K stars 👀 Watchers: 9 🍴 Forks: 131 forks 💻 Programming Languages: TypeScript - Svelte - Astro - Rust - CSS - JavaScript - HTML 🏷️ Related Topics:
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================================== 🧠 By: https://t.me/DataScienceM