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 68 482 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.
68 482
Subscribers
+724 hours
-597 days
-7530 days
Posts Archive
☄️ 46 Best Resources to Learn Data Structures and Algorithms including Online Courses, Tutorials, Books, and YouTube Videos 👇
⛓ https://www.mltut.com/best-resources-to-learn-data-structures-and-algorithms/
✈️ http://t.me/codeprogrammer ✅
😠 More likes 😠 ➡️ more posts
🚓 Deep Learning Roadmap 2024- Step-by-Step Career Path
Are you looking for a step-by-step Deep Learning Roadmap?… If yes, this article is for you. This article will provide a complete Deep Learning Roadmap from scratch. Along with that, you will also find some best resources to learn Deep Learning concepts.
Now without any further ado, let’s get started 👇
🔗 https://www.mltut.com/deep-learning-roadmap/
Very important 65p data science cheat sheets
https://www.patreon.com/posts/650-data-science-100466751
🐻Plotting with Pandas series 🐼
✅ https://t.me/codeprogrammer ✅
😡 More likes 😡 ➡️ more posts
Immediately play the official NotCoin game launched by Telegram. For every 10,000 points, you will earn one dollar.
https://t.me/notcoin_bot?start=r_574156_5692331
👨💻 My data science training source
👀 I have been taking courses related to data science, such as Python programming, machine learning, deep learning, natural language processing, etc. for several years, and after reviewing online courses, reading various books, educational blogs, etc. .. I decided to put all the content that made me progress during this time in the Github repo that I put the link below.
📂 Also, I have designed the scripts both in the presentation format (such as PowerPoint) and in the course notes format.
┌ 🏷 Teaching Data Science
└ 📂 GitHub-Repos
✅ https://t.me/codeprogrammer ✅
😡 More likes 😡 ➡️ more posts
🟢 7 valuable resources that I used to prepare for data science interviews!
🟢 One of the most important factors to get data science jobs in the best companies is success in job interviews.
🗂 I have put here 7 valuable resources that helped me a lot while preparing for data science interviews. I hope these resources can help you succeed in data science interviews
1️⃣ machine learning
📕 Link: Machine Learning
2️⃣ Python programming language
📕 Link: Python Programming Language
3️⃣ SQL programming language
📕 Link: SQL Programming Language
4️⃣ R programming language
📕 Link: R Programming Language
5️⃣ Pandas library
📕 Link: Pandas Python Library
6️⃣ NumPy library
📕 Link: NumPy Python Library
7️⃣ Matplotlib library
📕 Link: Matplotlib Python Library
✅ https://t.me/codeprogrammer ✅
😡 More likes 😡 ➡️ more posts
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┌ 🏷 Data Analysis for Social Scientists
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└ 🎬 Lecture Videos
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