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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

Network: Machine Learning with PythonIndia4 586Education2 406...

📈 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 68 482 subscribers, ranking 2 406 in the Education category and 4 586 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 68 482 subscribers.

According to the latest data from 04 November, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -75 over the last 30 days and by 7 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 3.38%. Within the first 24 hours after publication, content typically collects 1.57% reactions from the total number of subscribers.
Post reach: On average, each post receives 2 314 views. Within the first day, a publication typically gains 1 073 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 9.
Thematic interests: Content is focused on key topics such as insidead, learning, degree, evaluation, algorithm.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Learn 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 05 November, 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.

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68 482

Subscribers

+724 hours

-597 days

-7530 days

2 314

Post views

~ 1 07324 hours

~ 1 59648 hours

3.38%

Engagement rate

~ 2

Posts per day

Ads index

Posts Archive

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68 482

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🖥 Get domain name information using Python $pip install whois $pip install whois

>>> import whois
>>> domain = whois.query('google.com')

>>> print(domain.dict)
{
 'expiration_date': datetime.datetime(2020, 9, 14, 0, 0),
 'last_updated': datetime.datetime(2011, 7, 20, 0, 0),
 'registrar': 'MARKMONITOR INC.',
 'name': 'google.com',
 'creation_date': datetime.datetime(1997, 9, 15, 0, 0)
}

>>> print(domain.name)
google.com

>>> print(domain.expiration_date)
2024-09-14 00:00:00

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How to Perform Face Detection with Deep Learning Face detection is a computer vision problem that involves finding faces in photos. It is a trivial problem for humans to solve and has been solved reasonably well by classical feature-based techniques, such as the cascade classifier. More recently deep learning methods have achieved state-of-the-art results on standard benchmark face detection datasets. One example is the Multi-task Cascade Convolutional Neural Network, or MTCNN for short. In this tutorial, you will discover how to perform face detection in Python using classical and deep learning models. https://machinelearningmastery.com/how-to-perform-face-detection-with-classical-and-deep-learning-methods-in-python-with-keras/

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