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:📈 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 68 151 subscribers, ranking 2 379 in the Education category and 4 752 in the India region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 68 151 subscribers.
According to the latest data from 01 September, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 84 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 4.17%. Within the first 24 hours after publication, content typically collects 1.54% reactions from the total number of subscribers.
- Post reach: On average, each post receives 2 845 views. Within the first day, a publication typically gains 1 052 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 02 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.
68 151
Subscribers
+724 hours
+247 days
+8430 days
Posts Archive
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0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
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Find your location on Map using Python
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Understanding Probability Distributions for Machine Learning with Python
In machine learning, probability distributions play a fundamental role for various reasons: modeling uncertainty of information and data, applying optimization processes with stochastic settings, and performing inference processes, to name a few. Therefore, understanding the role and uses of probability distributions in machine learning is essential for designing robust machine learning models, choosing the right algorithms, and interpreting outputs of a probabilistic nature, especially when building models with machine learning-friendly programming languages like Python.
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In this learning path, you’ll get started with pandas and get to know the ins and outs of how you can use it to analyze data with Python.
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