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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 68 170 subscribers, ranking 2 376 in the Education category and 4 741 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 68 170 subscribers.

According to the latest data from 04 September, 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 23 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 2.50%. 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 1 707 views. Within the first day, a publication typically gains 1 071 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 05 September, 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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68 170
Subscribers
+2324 hours
+717 days
+7730 days
Posts Archive
🚀 Free Python Course with Certificate🚀 Unlock the world of coding with our Python Fundamentals for Beginners course—complet
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Repost from Data Science Books
Think Python (2024) Available here: https://t.me/+qvMSLM70zys1ZTJi
Think Python (2024) Available here: https://t.me/+qvMSLM70zys1ZTJi

Comprehensive Python Cheatsheet (2024) http://t.me/codeprogrammer 🔒 🔒 #deeplearning #AI #ML #python

Repost from Data Science Books
Dear Programmers, Engineers, and Students ❤️: We have two subscription plans: Free Plan: Available for subscribers of this channel. 🆓 The free plan includes: 💠 Up to 3 books daily with an average rating. 💠 One training course with an average rating each week. 💠 2 medium-rated programming projects. 🪙 Gold Plan: 🔒 More than 10 high-rated books. 🔒 One high-rated training course (Coursera, Udemy, and other popular platforms) every day. 🔒 Projects, resources, datasets, roadmaps, and important guides. 🔒 Support Team You can switch to the Gold Plan by subscribing monthly through this link 👇 https://t.me/+qvMSLM70zys1ZTJi 🔥 Cost of the Gold Plan subscription: 3$ per month. For any inquiries or issues you encounter with the subscription, please contact me at: t.me/husseinSheikho

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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

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☄️ JupyterLab Templates plugin 👨🏻‍💻 If you use JupyterLab a lot, you probably create a new notebook from scratch every time you start a data analysis project. But with the JupyterLab Templates plugin , there is no need to do this anymore. This tool allows you to create different templates and use them whenever you need. 💰 For example, suppose you have a similar structure for each data analysis or EDA project. Using JupyterLab Templates, you can create this structure once and then use that template every time you want to start a new project, without having to start all over again! ⏪ Installing and using this plugin is very simple.👇
pip install jupyterlab_templates
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Repost from Data Science Books
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