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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Network:π 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 68 579 subscribers, ranking 2 404 in the Education category and 4 688 in the India region.
π Audience metrics and dynamics
Since its creation on Π½Π΅Π²ΡΠ΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 68 579 subscribers.
According to the latest data from 25 October, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 227 over the last 30 days and by -9 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 3.45%. Within the first 24 hours after publication, content typically collects 1.52% reactions from the total number of subscribers.
- Post reach: On average, each post receives 2 369 views. Within the first day, a publication typically gains 1 042 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.
π Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
βLearn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
Admin: @HusseinSheikho || @Hussein_Sheikhoβ
Thanks to the high frequency of updates (latest data received on 26 October, 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.
68 579
Subscribers
-924 hours
-237 days
+22730 days
Posts Archive
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Repost from Machine Learning
I found a great resource for interactive learning about machine learning and AI β VizLearn.
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Repost from Machine Learning with Python
This channels is for Programmers, Coders, Software Engineers.
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A collection of explanations for key concepts and scientific papers in machine learning:
https://github.com/dair-ai/ML-Papers-Explained
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Repost from Machine Learning
Pandas vs Polars β 14-section course cheatshee
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Repost from Machine Learning with Python
This channels is for Programmers, Coders, Software Engineers.
0οΈβ£ Python
1οΈβ£ Data Science
2οΈβ£ Machine Learning
3οΈβ£ Data Visualization
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Repost from Machine Learning
Uniface
Automate face detection, recognition, and analysis of key facial landmarks with the Uniface Python library.
https://github.com/yakhyo/uniface
https://t.me/MachineLearning9
Repost from Machine Learning
OpenAI researcher Alice Liu went through 57 interviews before being hired, and then openly shared her entire preparation and job search journey.
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Mathematics:
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#Programming #Coding #Development #Tech #Python #DataScienceRepost from Learn Python Coding
Here's a small fact about Python π
The
:= operator is called the "walrus" because the symbols resemble the eyes and tusks of a walrus π¦
It was introduced in Python 3.8 and allows you to assign a value to a variable and use it directly within the expression at the same time.
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while (line := input("Say something: ")) != "quit":
print(f"You said: {line}")input(), and then check it.
Have you ever used the := operator in your code?
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