Machine Learning
前往频道在 Telegram
Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho
显示更多📈 Telegram 频道 Machine Learning 的分析概览
频道 Machine Learning (@machinelearning9) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 40 398 名订阅者,在 技术与应用 类别中位列第 3 324,并在 叙利亚 地区排名第 225 位。
📊 受众指标与增长动态
自 невідомо 创建以来,项目保持高速增长,吸引了 40 398 名订阅者。
根据 13 七月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 421,过去 24 小时变化为 25,整体触达仍然可观。
- 认证状态: 未认证
- 互动率 (ER): 平均受众互动率为 2.65%。内容发布后 24 小时内通常能获得 1.74% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 1 070 次浏览,首日通常累积 701 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 4。
- 主题关注点: 内容集中在 distance, insidead, gpu, learning, degree 等核心主题上。
📝 描述与内容策略
作者将该频道定位为表达主观观点的平台:
“Real Machine Learning — simple, practical, and built on experience.
Learn step by step with clear explanations and working code.
Admin: @HusseinSheikho || @Hussein_Sheikho”
凭借高频更新(最新数据采集于 14 七月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 技术与应用 类别中的关键影响点。
40 398
订阅者
+2524 小时
+1547 天
+42130 天
帖子存档
40 400
Repost from Machine Learning with Python
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✨ 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
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✨ 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
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✨ 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
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✨ 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
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✨ 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
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✨ 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
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✨ 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
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✨ 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
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✨ 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
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✨ 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
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✨ 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
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✨ 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
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✨ 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
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✨ 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
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✨ 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
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✨ 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
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✨ 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
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🔥 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
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🧠 By: https://t.me/DataScienceM
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🔥 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:
#svelte #tauri #tailwindcss #sveltekit================================== 🧠 By: https://t.me/DataScienceM
