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Machine Learning with Python

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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📈 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 68 103 名订阅者,在 教育 类别中位列第 2 374,并在 印度 地区排名第 4 765

📊 受众指标与增长动态

невідомо 创建以来,项目保持高速增长,吸引了 68 103 名订阅者。

根据 28 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 75,过去 24 小时变化为 -18,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 4.69%。内容发布后 24 小时内通常能获得 1.70% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 3 194 次浏览,首日通常累积 1 155 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 29 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。

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68 103
订阅者
-1824 小时
-907
+7530
帖子存档
200$ to 20k$ SOL Challenge! As promised, i will do another challenge for those who missed the previous one! Last one we compl
200$ to 20k$ SOL Challenge! As promised, i will do another challenge for those who missed the previous one! Last one we completed in 6 days, let’s do this one even quicker! Join my free group Before closing 👇 https://t.me/+DAKLP7eUy9Y3ZjY0 #ad InsideAds

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💛 Top 10 Best Websites to Learn Machine Learning ⭐️ by [@codeprogrammer] --- 🧠 Google’s ML Course 🔗 https://developers.google.com/machine-learning/crash-course 📈 Kaggle Courses 🔗 https://kaggle.com/learn 🧑‍🎓 Coursera – Andrew Ng’s ML Course 🔗 https://coursera.org/learn/machine-learning ⚡️ Fast.ai 🔗 https://fast.ai 🔧 Scikit-Learn Documentation 🔗 https://scikit-learn.org 📹 TensorFlow Tutorials 🔗 https://tensorflow.org/tutorials 🔥 PyTorch Tutorials 🔗 https://docs.pytorch.org/tutorials/ 🏛️ MIT OpenCourseWare – Machine Learning 🔗 https://ocw.mit.edu/courses/6-867-machine-learning-fall-2006/ ✍️ Towards Data Science (Blog) 🔗 https://towardsdatascience.com --- 💡 Which one are you starting with? Drop a comment below! 👇 #MachineLearning #LearnML #DataScience #AI #TechWithRam

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DS Interview.pdf1.57 MB

These Google Colab-notebooks help to implement all machine learning algorithms from scratch 🤯 Repo: https://udlbook.github.i
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These Google Colab-notebooks help to implement all machine learning algorithms from scratch 🤯 Repo: https://udlbook.github.io/udlbook/ 👉 @codeprogrammer

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Build your own AI agent from scratch for free in 5 minutes In this article, I will show you how to build your first AI agent from scratch using Google’s ADK (Agent Development Kit). This is an open-source framework that makes it easier to create agents, test them, add tools, and even build multi-agent systems. Read: https://habr.com/en/articles/974212/

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This repository collects everything you need to use AI and LLM in your projects. 120+ libraries, organized by development stages: → Model training, fine-tuning, and evaluation → Deploying applications with LLM and RAG → Fast and scalable model launch → Data extraction, crawlers, and scrapers → Creating autonomous LLM agents → Prompt optimization and security Repo: https://github.com/KalyanKS-NLP/llm-engineer-toolkit 🥺 https://t.me/DataAnalyticsX

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Machine Learning with Python - Telegram 频道 @codeprogrammer 的统计与分析