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Machine Learning

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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📈 Analytical overview of Telegram channel Machine Learning

Channel Machine Learning (@machinelearning9) in the English language segment is an active participant. Currently, the community unites 40 403 subscribers, ranking 3 324 in the Technologies & Applications category and 225 in the Syria region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 40 403 subscribers.

According to the latest data from 13 July, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 421 over the last 30 days and by 25 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 2.65%. Within the first 24 hours after publication, content typically collects 1.74% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 070 views. Within the first day, a publication typically gains 701 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 4.
  • Thematic interests: Content is focused on key topics such as distance, insidead, gpu, learning, degree.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho

Thanks to the high frequency of updates (latest data received on 14 July, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.

40 403
Subscribers
+2524 hours
+1547 days
+42130 days
Posts Archive
Repost from Data Analytics
📌 How to Create a Real-Time Gesture-to-Text Translator Using Python and Mediapipe ✍️ OMOTAYO OMOYEMI 🏷️ #Computer_Vision
📌 How to Create a Real-Time Gesture-to-Text Translator Using Python and Mediapipe ✍️ OMOTAYO OMOYEMI 🏷️ #Computer_Vision

✨ Training YOLOv12 for Detecting Pothole Severity Using a Custom Dataset ✨ 📖 Table of Contents Training YOLOv12 for Detectin
✨ Training YOLOv12 for Detecting Pothole Severity Using a Custom Dataset ✨ 📖 Table of Contents Training YOLOv12 for Detecting Pothole Severity Using a Custom Dataset Introduction Dataset and Task Overview About the Dataset What Are We Detecting? Defining Pothole Severity Can the Pothole Severity Logic Be Improved? Configuring Your Development Environment Training…... 🏷️ #ComputerVision #DeepLearning #ObjectDetection #Tutorial #YOLO

✨ 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

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#testing #php #framework #pest
================================== 🧠 By: https://t.me/DataScienceM

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================================== 🧠 By: https://t.me/DataScienceM

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================================== 🧠 By: https://t.me/DataScienceM

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#neon #wasm #avx #simd #intrinsics #avx2 #simd_programming #avx512 #simd_parallelism #simd_instructions #simd_library #sse42 #avx_instructions #simd_intrinsics #avx_512
================================== 🧠 By: https://t.me/DataScienceM

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================================== 🧠 By: https://t.me/DataScienceM

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================================== 🧠 By: https://t.me/DataScienceM

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================================== 🧠 By: https://t.me/DataScienceM

🔥 Trending Repository: winapps 📝 Description: Run Windows apps such as Microsoft Office/Adobe in Linux (Ubuntu/Fedora) and
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================================== 🧠 By: https://t.me/DataScienceM

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================================== 🧠 By: https://t.me/DataScienceM

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================================== 🧠 By: https://t.me/DataScienceM