Machine Learning

Open in Telegram

Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho

Network:Machine Learning with Python Syria215 Technologies & Applications3 145...

📈 Analytical overview of Telegram channel Machine Learning

Channel Machine Learning (@machinelearning9) in the English language segment is an active participant. Currently, the community unites 41 668 subscribers, ranking 3 145 in the Technologies & Applications category and 215 in the Syria region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 41 668 subscribers.

According to the latest data from 05 October, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 533 over the last 30 days and by 13 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 6.25%. Within the first 24 hours after publication, content typically collects 1.92% reactions from the total number of subscribers.
Post reach: On average, each post receives 2 601 views. Within the first day, a publication typically gains 800 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 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 October, 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.

Buy Ad

41 668

Subscribers

+1324 hours

+1357 days

+53330 days

2 601

Post views

~ 80024 hours

~ 1 20948 hours

6.25%

Engagement rate

~ 1

Posts per day

Ads index

beta

Posts Archive

41 668

Repost from Machine Learning with Python

🎓 $10,000 Scholarship Grant — Yours for the Taking! 🎓 Imagine this: $10,000 handed to you — completely FREE — to fund your education. No essays. No essays. No application fees. Just your effort inside our bot. 💸 🏆 Reach 10,000 points and the scholarship is yours. 🎁 Plus, you unlock a lifetime subscription to all our paid courses & books — yours forever. Here's how easy it is to earn points: 🔗 Invite friends with your referral link → +50 points each 📺 Watch ads → +15 points per ad 🧠 Answer the Question of the Day → +15 points Every small action gets you closer to that $10,000. Every friend you invite doubles your chance. Every question you answer sharpens your mind AND your wallet. 🚀 Don't wait. Start now: 👉 https://t.me/UdemySybot?start=ref_148350890 The next scholarship winner could be you. All it takes is 10,000 points — and the discipline to start today. 🔥 Your future self will thank you. 🔥

41 668

https://t.me/UdemySybot?start=ref_418788114 Get Free Courses 😁

41 668

"Learning Mathematics: Why Memory, Practice, and Technique are More Important than Talent" To master mathematics, it is necessary to memorize a large amount of information, rules, methods of simplification, and problem-solving techniques. There is no other way. Theory is useful, but in moderation. It's like learning a language. If you focus too much on grammar, you will never learn to speak it fluently. https://algebrica.org/learning-mathematics/

41 668

Repost from Machine Learning with Python

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_rRW2scgfRhOTc0 ✅ https://t.me/Codeprogrammer

41 668

Repost from Machine Learning with Python

"How to Train a Neural Network" is a concise summary of the MIT course lectures on deep learning from 2024. It focuses on one of the fundamental questions in neural networks: how a model learns its weights. The summary examines the training process from a mathematical perspective. It covers topics such as forward propagation, loss functions, gradients, backpropagation, and gradient-based optimization methods. I believe this is an interesting resource for those who want to go beyond a general, intuitive understanding of neural networks and begin to delve into the mathematics that underlies their training. https://ocw.mit.edu/courses/6-7960-deep-learning-fall-2024/mit6_7960_f24_lec2.pdf https://t.me/CodeProgrammer 🤩

41 668

https://t.me/UdemySybot?start=ref_418788114 🎓 Free Udemy courses every day — join me!

41 668

pandas_vs_polars_cheatsheet.png1.05 MB

41 668

Repost from Machine Learning with Python

If you're just starting to learn machine learning and want to delve deeper into the mathematics required for machine learning and deep learning, I recommend trying this platform. It's something like LeetCode for machine learning. This is not an advertisement: I personally used it and decided to share it with you. https://deep-ml.com https://t.me/CodeProgrammer

41 668

Repost from Machine Learning with Python

41 668

🤖 A Practical Tip for ML Data Collection When building a machine learning project, getting enough useful data is often just as important as the model itself. If you're collecting public web data for a dataset, you may need to access the same source from different locations or test how location affects the data returned. A residential proxy can help with this by routing your requests through IPs from different regions. For example, with Python:

import requests

proxies = {
    "http": "http://USER:PASSWORD@HOST:PORT",
    "https": "http://USER:PASSWORD@HOST:PORT"
}

response = requests.get(
    "https://example.com",
    proxies=proxies
)

print(response.status_code)

Replace USER, PASSWORD, HOST, and PORT with your proxy credentials. 🚀 711Proxy provides real residential IPs across 200+ countries and regions, with SOCKS5 support and sticky sessions — useful for data collection, testing, and other location-based ML workflows. 🎁 1GB free for testing New users can use 711TRIAL to get 1GB of residential proxy traffic. 👉 https://www.711proxy.com After registration, contact 711Proxy support and mention “711TRIAL” to claim the trial. Available to eligible new users.

41 668