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Machine Learning
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Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho
Show more📈 Analytical overview of Telegram channel Machine Learning
Channel Machine Learning (@machinelearning9) in the English language segment is an active participant. Currently, the community unites 39 904 subscribers, ranking 3 434 in the Technologies & Applications category and 240 in the Syria region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 39 904 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 482 over the last 30 days and by 19 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 3.06%. Within the first 24 hours after publication, content typically collects 1.66% reactions from the total number of subscribers.
- Post reach: On average, each post receives 1 222 views. Within the first day, a publication typically gains 662 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
- Thematic interests: Content is focused on key topics such as distance, insidead, gpu, learning, degree.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“Real Machine Learning — simple, practical, and built on experience.
Learn step by step with clear explanations and working code.
Admin: @HusseinSheikho || @Hussein_Sheikho”
Thanks to the high frequency of updates (latest data received on 06 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 Technologies & Applications category.
39 904
Subscribers
+1924 hours
+1307 days
+48230 days
Data loading in progress...
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| Date | Subscriber Growth | Mentions | Channels | |
| 06 June | +11 | |||
| 05 June | +24 | |||
| 04 June | +24 | |||
| 03 June | +26 | |||
| 02 June | +33 | |||
| 01 June | +31 |
Channel Posts
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Those studying ML through dozens of random tabs and unclosed playlists may find this repository useful for organizing their learning. 📚
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| 12 | Optimizing the model's performance through Prompt Tuning with the PEFT library.
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