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 Python India5 036 Education2 429...

📈 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 67 826 subscribers, ranking 2 429 in the Education category and 5 036 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 67 826 subscribers.

According to the latest data from 14 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 66 over the last 30 days and by 5 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 4.52%. Within the first 24 hours after publication, content typically collects 1.70% reactions from the total number of subscribers.
Post reach: On average, each post receives 3 064 views. Within the first day, a publication typically gains 1 155 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 5.
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 15 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.

67 826

Subscribers

+524 hours

No data7 days

+6630 days

3 064

Post views

~ 1 15524 hours

~ 1 68748 hours

4.52%

Engagement rate

~ 4

Posts per day

Ads index

beta

Posts Archive

67 832

Repost from Data Science Books

We have just launched a fundraising campaign for the channel to ensure continued quality service We upload the book via Internet data, and this is expensive for us Participate and contribute to the donation campaign until the target amount is reached Members who will contribute to the donation campaign will receive a free subscription to the paid channel and a LinkedIn grant Donate link: https://boosty.to/datascienceteam/donate

67 832

Repost from Data Science Books

We have just launched a fundraising campaign for the channel to ensure continued quality service We upload the book via Internet data, and this is expensive for us Participate and contribute to the donation campaign until the target amount is reached Donate link: https://boosty.to/datascienceteam/donate

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غدا سنطلق حملة جمع تبرعات للقناة، وسيتم عرض نسبة التقدم أولا من خلال رسالة مثبتة نأمل منكم المشاركة في التبرعات إذا كنتم قادرين على التبرع Tomorrow we will launch a fundraising campaign for the channel, and the progress rate will be displayed first through a pinned message We hope that you will participate in donations if you are able to donate

67 832

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🔥 Free Certification Courses from Google to try in 2023. 1. Basics of Machine Learning https://grow.google/intl/en_in/ 2. Machine Learning Crash Course https://coursya.com/product/machine-learning-crash-course 3. Project Execution: Running the Project https://coursera.org/learn/project-execution-google 4. Foundations of Project Management https://coursera.org/learn/project-management-foundations 5. Project Initiation: Starting a Successful Project https://coursera.org/learn/project-initiation-google 6. Project Planning: Putting It All Together https://coursera.org/learn/project-planning-google 7. Google Analytics for Power Users https://coursya.com/product/google-analytics-certification-coursya 8. Fundamentals of digital marketing https://skillshop.exceedlms.com/student/collection/654330-digital-marketing?locale=en-GB 9. Python Basics for Data Analysis https://coursya.com/product/learn-python-basics-for-data-analysis 10. Data Science Foundations https://grow.google/intl/en_in/ 11. Advanced Google Analytics https://coursera.org/professional-certificates/google-data-analytics 12. Google Cloud Computing Foundations: https://cloudskillsboost.google/course_templates/153 13. Data, ML, and AI in Google Cloud https://coursya.com/product/google-cloud-computing-foundations-data-ml-and-ai-in-google-cloud-google-cloud-skills-boost 14. Agile Project Management https://coursera.org/learn/agile-project-management 15. Google Project Management https://coursera.org/professional-certificates/google-project-management https://t.me/CodeProgrammer Please more 100 👍 with our posts

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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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💼 Briefcase Briefcase is a tool for converting a Python project into a standalone native application. ▪ Github: https://github.com/beeware/briefcase ▪Tutorial: https://briefcase.readthedocs.io/en/stable/ https://t.me/CodeProgrammer Please more reaction with our posts

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