Machine Learning with Python

前往频道在 Telegram

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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网络:Machine Learning with Python 印度5 049 教育2 404...

📈 Telegram 频道 Machine Learning with Python 的分析概览

频道 Machine Learning with Python (@codeprogrammer) 英语语言赛道中的是活跃参与者。目前社区聚集了 67 821 名订阅者，在教育类别中位列第 2 404，并在印度地区排名第 5 049 位。

📊 受众指标与增长动态

自 невідомо 创建以来，项目保持高速增长，吸引了 67 821 名订阅者。

根据 05 六月, 2026 的最新数据，频道保持稳定运转。过去 30 天订阅人数变化为 77，过去 24 小时变化为 9，整体触达仍然可观。

认证状态： 未认证
互动率 (ER)： 平均受众互动率为 2.60%。内容发布后 24 小时内通常能获得 2.50% 的反应，占订阅者总量。
帖子覆盖： 每篇帖子平均可获得 1 767 次浏览，首日通常累积 1 695 次浏览。
互动与反馈： 受众积极参与，单帖平均反应数为 6。
主题关注点： 内容集中在 insidead, learning, degree, evaluation, algorithm 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台：
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho”

凭借高频更新（最新数据采集于 07 六月, 2026），频道始终保持新鲜度与高覆盖。分析显示受众积极互动，使其成为教育类别中的关键影响点。

67 821

订阅者

+924 小时

+587 天

+7730 天

1 767

帖子浏览量

~ 1 69524 小时

~ 2 25748 小时

2.60%

参与率

~ 3

每日帖子数

Ads index

beta

帖子存档

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Have you tried running the code? yes 👍 | No 👎

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Create a Wi-Fi QR code in Python in a couple of seconds

pip install wifi_qrcode_generator

import wifi_qrcode_generator.generator
from PIL import Image

ssid = "CLCoding_WIFI"
password = "supersecret123"
security = "WPA"

from wifi_qrcode_generator.generator import wifi_qrcode
qr = wifi_qrcode(ssid, False, security, password)

qr.make_image().save("wifi_qr.png")
Image.open("wifi_qr.png")

👉 @codeprogrammer

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❔ Interview question What do globals() and locals() do? Answer: Functions globals() and locals() return a dictionary with variables of the current scope. ▶️ globals() — provides access to all global names in the current module (i.e., variables, functions, and classes defined at the top level) ▶️ locals() — returns local variables in the current context: inside a function, class, or block They are useful for dynamic analysis, debugging, metaprogramming, and when working with eval() / exec(). tags: #interview ➡ @codeprogrammer

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Your interaction with us drives us more free information and knowledge

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This GitHub repo is a gold mine for EVERY data scientist! (full of hands-on and interactive tutorials) DS Interactive Python provides several dashboards to interactively learn about statistics, ML models, and other related theoretical concepts! Some key topics you can understand interactively: • PCA • Bagging and boosting • Linear regression and OLS • Bayesian and frequentist statistics • confidence intervals • clustering (kmeans, spectral clustering, etc.) • central limit theorem • neural networks (the backpropagation animation is really good) • and many more. Link: https://github.com/GeostatsGuy/DataScienceInteractivePython https://t.me/CodeProgrammer

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Repost from Python Courses & Resources

Create artificial intelligence using Python In the video the author explains the basics of neural networks and shows how to implement your own simple #AI from scratch in #Python

https://t.me/Python53

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Repost from Machine Learning with Python

🚀 THE 7-DAY PROFIT CHALLENGE! 🚀 Can you turn $100 into $5,000 in just 7 days? Lisa can. And she’s challenging YOU to do the same. 👇 https://t.me/+AOPQVJRWlJc5ZGRi https://t.me/+AOPQVJRWlJc5ZGRi https://t.me/+AOPQVJRWlJc5ZGRi

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Data Science Formulas Cheat Sheet.pdf1.75 KB

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https://t.me/DataScienceY

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Comprehensive Python Cheatsheet This Comprehensive #Python Cheatsheet brings together core syntax, data structures, functions, #OOP, decorators, regular expressions, libraries, and more — neatly organized for quick reference and deep understanding.

https://t.me/CodeProgrammer

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