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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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📈 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 67 812 subscribers, ranking 2 404 in the Education category and 5 049 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 67 812 subscribers.

According to the latest data from 05 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 77 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 2.60%. Within the first 24 hours after publication, content typically collects 2.50% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 767 views. Within the first day, a publication typically gains 1 695 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.

📝 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 07 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.

67 812
Subscribers
+924 hours
+587 days
+7730 days
Posts Archive
nature papers: 1400$ Q1 and  Q2 papers    900$ Q3 and Q4 papers   500$ Doctoral thesis (complete)    700$ M.S thesis         300$ paper simulation   200$ Contact me https://t.me/m/-nTmpj5vYzNk

200$ to 20k$ SOL Challenge! As promised, i will do another challenge for those who missed the previous one! Last one we compl
200$ to 20k$ SOL Challenge! As promised, i will do another challenge for those who missed the previous one! Last one we completed in 6 days, let’s do this one even quicker! Join my free group Before closing 👇 https://t.me/+DAKLP7eUy9Y3ZjY0 #ad InsideAds

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Python Object-Oriented Programming - 5e 2025 Available here free https://signal.group/#CjQKIPcpEqLQow53AG7RHjeVk-4sc1TFxyym3r
Python Object-Oriented Programming - 5e 2025 Available here free https://signal.group/#CjQKIPcpEqLQow53AG7RHjeVk-4sc1TFxyym3r0gQQzV-OPpEhCPw_-kRmJ8LlC13l0WiEfp

This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visua
This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visualization 4️⃣ Artificial Intelligence 5️⃣ Data Analysis 6️⃣ Statistics 7️⃣ Deep Learning 8️⃣ programming Languages ✅ https://t.me/addlist/8_rRW2scgfRhOTc0https://t.me/Codeprogrammer

Learn how LLMs work in less than 10 minutes And honestly? This is probably the best visualization of #LLMs ever made. https://t.me/Python53

“I almost lost my main accounts to bans—until I found this.” Managing dozens of profiles seemed impossible. Then I tried GoLo
“I almost lost my main accounts to bans—until I found this.” Managing dozens of profiles seemed impossible. Then I tried GoLogin: safe, fast, and insanely reliable. Thousands already trust it to run ads without fear. Ready to change how you manage accounts? Try it here before your competitors do. #ad InsideAds

Awesome open-source project to learn more about Generative Adversarial Networks. We found this interactive website that shows
Awesome open-source project to learn more about Generative Adversarial Networks. We found this interactive website that shows you visually how #GANs work. GAN Lab Website: https://lnkd.in/eYV8QvrJ https://t.me/CodeProgrammer 🩷

For those interested in joining our Premium channel, which contains over 5,000 books and 200 courses in machine learning, programming languages, data analysis, LLM, and other related fields with daily updates> We offer a 15-minute free trial to explore the channel's content. Afterward, you can subscribe to the channel for $50 – a permanent subscription. Contact me: t.me/HusseinSheikho

All assignments for the #Stanford The Modern Software Developer course are now available online. This is the first full-fledg
All assignments for the #Stanford The Modern Software Developer course are now available online. This is the first full-fledged university course that covers how code-generative #LLMs are changing every stage of the development lifecycle. The assignments are designed to take you from a beginner to a confident expert in using AI to boost productivity in development. Enjoy your studies! ✌️ (https://github.com/mihail911/modern-software-dev-assignments

I never believed a simple bot could change my workflow — until I met @MegaRenamerV2Bot. It renames thousands of MEGA files in
I never believed a simple bot could change my workflow — until I met @MegaRenamerV2Bot. It renames thousands of MEGA files in seconds, saving me hours every day. No more manual hassle, just pure efficiency. Curious how it works? Discover the secret here 👉 https://t.me Join RSC Bots and step up your file game! #ad InsideAds

How to test code without a real database During unit testing, connecting to a real DB is unnecessary: • tests run slowly • be
How to test code without a real database
During unit testing, connecting to a real DB is unnecessary: • tests run slowly • become unstable • require a working server
It is much better to mock the call to pandas.read_sql and return dummy data Example function:
def query_user_data(user_id):
    query = f"SELECT id, name FROM users WHERE id = {user_id}"
    return pd.read_sql(query, "postgresql://localhost/mydb")
Test with mock:
from unittest.mock import patch
import pandas as pd

@patch("pandas.read_sql")
def test_database_query_mocked(mock_read_sql):
    mock_read_sql.return_value = pd.DataFrame(
        {"id": [123], "name": ["Alice"]}
    )

    result = query_user_data(user_id=123)
    assert result["name"].iloc[0] == "Alice"
This way you test only the business logic — quickly, reliably, and without unnecessary dependencies https://t.me/CodeProgrammer

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200$ to 20k$ SOL Challenge! As promised, i will do another challenge for those who missed the previous one! Last one we compl
200$ to 20k$ SOL Challenge! As promised, i will do another challenge for those who missed the previous one! Last one we completed in 6 days, let’s do this one even quicker! Join my free group Before closing 👇 https://t.me/+DAKLP7eUy9Y3ZjY0 #ad InsideAds

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Кринжовые танцы, снег, пародия на Стекловату — полный набор классного новогоднего поздравления от приложения для общения с друзьями 🎄 https://t.me/blinkmap/1110