Python Courses & Resources
前往频道在 Telegram
Master Python with step-by-step courses – from basics to advanced projects and practical applications.
显示更多📈 Telegram 频道 Python Courses & Resources 的分析概览
频道 Python Courses & Resources (@python53) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 49 038 名订阅者,在 教育 类别中位列第 3 603,并在 印度 地区排名第 7 917 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 49 038 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 494,过去 24 小时变化为 15,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 2.39%。内容发布后 24 小时内通常能获得 1.24% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 1 172 次浏览,首日通常累积 608 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 3。
- 主题关注点: 内容集中在 consultation, dentist, insidead, waybienad, appointment 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:
“Master Python with step-by-step courses – from basics to advanced projects and practical applications.”
凭借高频更新(最新数据采集于 06 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。
49 038
订阅者
+1524 小时
+1457 天
+49430 天
帖子存档
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Repost from Machine Learning with Python
🗂 Building our own mini-Skynet — a collection of 10 powerful AI repositories from big tech companies
1. Generative AI for Beginners and AI Agents for Beginners
Microsoft provides a detailed explanation of generative AI and agent architecture: from theory to practice.
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Step-by-step assembly of your own GPT to understand how LLMs are structured "under the hood".
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An official set of examples for working with APIs, RAG systems, and integrating AI into production from OpenAI.
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Classic tools for computer vision and image generation from Meta and the CompVis research team.
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A powerful resource for Python and data analysis.
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Ready-made app templates with LLMs and a structured course on classic machine learning.
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Machine Learning Foundations: Probability
📝 Get an in-depth introduction to probability, find out why its a prerequisite for machine learning, and learn how to use it to design and implement machine learning algorithms.
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🔰 Level: Beginner
⏰ Duration: 1h 24m
Repost from Machine Learning with Python
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Python Interview Questions & Mock Tests – 2026
Practice tests covering Python basics, OOP, advanced concepts, libraries, debugging, and real interview-level questions...
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🔅 Deep Learning with Python: Convolutional Neural Networks
📝 Gain hands-on experience building, training, and evaluating convolutional neural networks (CNNs) using Python for image classification, object detection, and segmentation.
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现已上线!2025 年 Telegram 研究 — 年度关键洞察 
