Artificial Intelligence

前往频道在 Telegram

🔒 Welcome Artificial Intelligence Channel Buy ads: https://telega.io/c/Artificial_Intelligence_COM

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网络:Zero To Mastery 印度4 348 技术与应用1 719...

📈 Telegram 频道 Artificial Intelligence 的分析概览

频道 Artificial Intelligence (@artificial_intelligence_com) 英语语言赛道中的是活跃参与者。目前社区聚集了 72 425 名订阅者，在 技术与应用 类别中位列第 1 719，并在印度地区排名第 4 348 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 72 425 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 405，过去 24 小时变化为 -37，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 6.63%。内容发布后 24 小时内通常能获得 1.94% 的反应，占订阅者总量。
帖子覆盖： 每篇帖子平均可获得 4 801 次浏览，首日通常累积 1 407 次浏览。
互动与反馈： 受众积极参与，单帖平均反应数为 11。
主题关注点： 内容集中在 learning, linkedin, linux, udemy, 040k| 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：
“🔒 Welcome Artificial Intelligence Channel Buy ads: https://telega.io/c/Artificial_Intelligence_COM”

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 技术与应用 类别中的关键影响点。

72 425

订阅者

-3724 小时

-1227 天

+40530 天

4 801

帖子浏览量

~ 1 40724 小时

~ 1 86648 小时

6.63%

参与率

~ 1

每日帖子数

Ads index

beta

帖子存档

72 425

--- Part 3: Classification ---

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05 - Simple Linear Regression.zip211.07 MB

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--- Part 2: Regression ---

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02 - Data Preprocessing.zip25.55 MB

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--- Part 1: Data Preprocessing ---

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01_Welcome_to_the_course!_Here_we_will_help_you_get_started_in_the.zip48.19 MB

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🔰 Machine Learning A-Z [2026]: AI, AWS, Python & R + LLM Prize 🌟 4.5 - 203785 votes 💰 Original Price: $64.99 📖 Learn to create Machine Learning Algorithms in Python, R and AWS from two Data Science experts. Code templates included. 🔊 Taught By: Kirill Eremenko, Hadelin de Ponteves 📤 Download Full Course 📤 Download All Courses

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Time Complexity of 10 Most Popular ML Algorithms

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🖥 Mindmap to learn machine learning

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🖥 Plexe 🛠 Plexe is a system that simplifies the creation of machine learning models by allowing users to describe their intent in natural language. 🔰 The system automatically generates functional models and is available as a Python library and cloud service. 🔰 Custom models are defined through a description including intent and input-output patterns, and can be created by a single team with support for distributed training using Ray. 🔰 Additionally, Plexe offers synthetic data generation and automatic schema inference features, supporting various LLM providers such as OpenAI and Anthropic. 🔗Links: https://github.com/plexe-ai/plexe

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Learning n8n from scratch

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