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:📈 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 68 138 名订阅者，在 教育 类别中位列第 2 366，并在 印度 地区排名第 4 740 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 68 138 名订阅者。
根据 30 八月, 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 86，过去 24 小时变化为 27，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 4.07%。内容发布后 24 小时内通常能获得 1.52% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 2 775 次浏览，首日通常累积 1 037 次浏览。
- 互动与反馈： 受众积极参与，单帖平均反应数为 5。
- 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 31 八月, 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。
68 138
订阅者
+2724 小时
-297 天
+8630 天
帖子存档
Repost from Machine Learning
📌 How to Build a Genetic Algorithm from Scratch in Python
🗂 Category: DATA SCIENCE
🕒 Date: 2024-08-30 | ⏱️ Read time: 16 min read
A complete walkthrough on how one can build a Genetic Algorithm from scratch in Python,…
Repost from Github Top Repositories
Python library RetinaFace for face detection and working with key points (eyes, nose, mouth)
Supports face alignment, easily installed via
pip install retina-face, and works based on deep models from the insightface project.
An excellent tool for tasks in computer vision and face recognition.
Usage examples:
from retinaface import RetinaFace
resp = RetinaFace.detect_faces("img1.jpg")
print(resp)
{
"face_1": {
"score": 0.9993440508842468,
"facial_area": [155, 81, 434, 443],
"landmarks": {
"right_eye": [257.82974, 209.64787],
"left_eye": [374.93427, 251.78687],
"nose": [303.4773, 299.91144],
"mouth_right": [228.37329, 338.73193],
"mouth_left": [320.21982, 374.58798]
}
}
}
Creating QR codes with Python in just a few lines of code
Anyone can generate their own QR code for a link, text, or even Wi-Fi data.
For this, the
qrcode library and the PIL module are used
pip install qrcode pillowimport qrcode
from PIL import Image
data = input("Enter data for QR: ")
qr = qrcode.QRCode(version=3, box_size=8, border=4)
qr.add_data(data)
qr.make(fit=True)
image = qr.make_image(fill="black", back_color="aqua")
image.save("qr_code.png")
Image.open("qr_code.png")Repost from Machine Learning
📌 A Guide to Clustering Algorithms
🗂 Category: DATA SCIENCE
🕒 Date: 2024-09-06 | ⏱️ Read time: 6 min read
An overview of clustering and the different families of clustering algorithms.
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Repost from Machine Learning
📌 Image Segmentation With K-Means Clustering
🗂 Category: MACHINE LEARNING
🕒 Date: 2024-09-05 | ⏱️ Read time: 11 min read
An introduction with Python
Google Collab notebooks to learn everything you need to master prompt engineering with Claude - from basic structure and role prompting to advanced techniques like few-shot learning, avoiding hallucinations, and tool use.
Perfect interactive lessons to level up your AI skills
Link: https://github.com/anthropics/courses/tree/master/prompt_engineering_interactive_tutorial/Anthropic%201P
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Harvard's "Advanced Algorithms"
by Jelani Nelson
📽 Lecture Videos: https://youtube.com/playlist?list=PL2SOU6wwxB0uP4rJgf5ayhHWgw7akUWSf
📷 Lecture Notes: https://people.seas.harvard.edu/~cs224/fall14/lec.html
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Repost from Machine Learning
📌 A Basic Introduction to Quantum GANs
🗂 Category: MACHINE LEARNING
🕒 Date: 2024-09-21 | ⏱️ Read time: 11 min read
“Quantum computing just becomes vastly simpler once you take the physics out of it.”
Repost from Machine Learning
📌 How to Build Effective Agentic Systems with LangGraph
🗂 Category: AGENTIC AI
🕒 Date: 2025-09-30 | ⏱️ Read time: 12 min read
Create AI workflows with agentic frameworks
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
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✅ https://t.me/Codeprogrammer
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