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Machine Learning with Python

Machine Learning with Python

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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho

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πŸ“ˆ Analytical overview of Telegram channel Machine Learning with Python

Channel Machine Learning with Python (@codeprogrammer) in the English language segment is an active participant. Currently, the community unites 67 813 subscribers, ranking 2 417 in the Education category and 5 033 in the India region.

πŸ“Š Audience metrics and dynamics

Since its creation on Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 67 813 subscribers.

According to the latest data from 11 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 56 over the last 30 days and by 0 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 3.96%. Within the first 24 hours after publication, content typically collects 2.43% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 2 683 views. Within the first day, a publication typically gains 1 650 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 6.
  • Thematic interests: Content is focused on key topics such as insidead, learning, degree, evaluation, algorithm.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œLearn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho”

Thanks to the high frequency of updates (latest data received on 12 June, 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 Education category.

67 813
Subscribers
No data24 hours
-127 days
+5630 days
Posts Archive
Python password generator πŸ–₯ #python #programming #developer #programmer #coding #coder #softwaredeveloper #computerscience #
Python password generator πŸ–₯ #python #programming #developer #programmer #coding #coder #softwaredeveloper #computerscience #webdev #webdeveloper #webdevelopment #pythonprogramming #pythonquiz #ai #ml #machinelearning #datascience https://t.me/CodeProgrammer 🐍

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DS CHEAT SHEET PANDAS 🐼 #MachineLearning #Pands #DeepLearning #ArtificialIntelligence #AI #Algorithms #Python https://t.me/CodeProgrammer 🐍

Important [ Python Built-in Methods ] {CheatSheet} #MachineLearning #NeuralNetwork #DeepLearning #ArtificialIntelligence #AI
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Important [ Python Built-in Methods ] {CheatSheet} #MachineLearning #NeuralNetwork #DeepLearning #ArtificialIntelligence #AI #Algorithms #python https://t.me/CodeProgrammer 🐍

πŸ–₯ Large Language Model Course The popular free LLM course has just been updated. This is a step-by-step guide with useful re
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πŸ–₯ Large Language Model Course The popular free LLM course has just been updated. This is a step-by-step guide with useful resources and notebooks for both beginners and those who already have an ml-base. The course is divided into 3 parts: 1️⃣ LLM Fundamentals : The block provides fundamental knowledge of mathematics, Python and neural networks. 2️⃣ LLM Scientist : This block focuses on the internal structure of LLMs and their creation using the latest technologies and frameworks. 3️⃣ The LLM Engineer : Here you will learn how to write applications in a hands-on way and how to deploy them. ⭐️ 41.4k stars on Github πŸ“Œ https://github.com/mlabonne/llm-course #llm #course #opensource #ml https://t.me/CodeProgrammer πŸ‘‘

To generate stunning maps from OpenStreetMap data in #Python, use Prettymaps. It enables map creation with minimal code and o
To generate stunning maps from OpenStreetMap data in #Python, use Prettymaps. It enables map creation with minimal code and offers versatile customization options. πŸš€ Link to Prettymaps: bit.ly/3Ps02Qj πŸ”– Dive deeper into the post: bit.ly/3PxxJjm https://t.me/CodeProgrammer β˜„οΈ

Machine Learning concepts - Intermediate Level. Convolutional Neural Network (CNN) Layers: Convolution vs Pooling vs Fully Co
Machine Learning concepts - Intermediate Level. Convolutional Neural Network (CNN) Layers: Convolution vs Pooling vs Fully Connected #MachineLearning #NeuralNetwork #DeepLearning #ArtificialIntelligence #AI #Algorithms https://t.me/CodeProgrammer 🐍

Machine Learning Algorithm basics! Support Vector Machines (SVM) vs k-Nearest Neighbors (k-NN) #MachineLearning #algorithms #
Machine Learning Algorithm basics! Support Vector Machines (SVM) vs k-Nearest Neighbors (k-NN) #MachineLearning #algorithms #ML #DataScience #ArtificialIntelligence #AI https://t.me/CodeProgrammer 🐍

Voice Recorder in #Python https://t.me/CodeProgrammer 🐍
Voice Recorder in #Python https://t.me/CodeProgrammer 🐍

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Check if Instagram or Facebook is down using Python
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