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Data science/ML/AI

Data science/ML/AI

前往频道在 Telegram

Data science and machine learning hub Python, SQL, stats, ML, deep learning, projects, PDFs, roadmaps and AI resources. For beginners, data scientists and ML engineers 👉 https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatascientist

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📈 Telegram 频道 Data science/ML/AI 的分析概览

频道 Data science/ML/AI (@datascience_bds) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 13 674 名订阅者,在 技术与应用 类别中位列第 9 377,并在 印度 地区排名第 31 635

📊 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 13 674 名订阅者。

根据 09 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 155,过去 24 小时变化为 5,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 8.03%。内容发布后 24 小时内通常能获得 2.25% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 1 098 次浏览,首日通常累积 308 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 panda, learning, row, api, ethic 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:
Data science and machine learning hub Python, SQL, stats, ML, deep learning, projects, PDFs, roadmaps and AI resources. For beginners, data scientists and ML engineers 👉 https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatasci...

凭借高频更新(最新数据采集于 10 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 技术与应用 类别中的关键影响点。

13 674
订阅者
+524 小时
+197
+15530
帖子存档
Machine Learning for Everyone.pdf4.60 MB

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Logistic regression

Data Science Cheat sheet 2.0 A helpful 5-page data science cheatsheet to assist with exam reviews, interview prep, and anything in-between. It covers over a semester of introductory machine learning, and is based on MIT's Machine Learning courses 6.867 and 15.072. The reader should have at least a basic understanding of statistics and linear algebra, though beginners may find this resource helpful as well. Creator: Aaron Wang Stars ⭐️: 4.5k Forked By: 645 https://github.com/aaronwangy/Data-Science-Cheatsheet #datascience ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ Join @datascience_bds for more cool repositories. *This channel belongs to @bigdataspecialist group

Process of Data Analysis
Process of Data Analysis

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Data Analytics Career Path
Data Analytics Career Path

Scientific Data Processing by Google Cloud Platform Big data, machine learning, and scientific data? It sounds like the perfect match. In this advanced-level quest, you will get hands-on practice with GCP services like Big Query, Dataproc, and Tensorflow by applying them to use cases that employ real-life, scientific data sets. By getting experience with tasks like earthquake data analysis and satellite image aggregation, Scientific Data Processing will expand your skill set in big data and machine learning so you can start tackling your own problems across a spectrum of scientific disciplines. Syllabus includes following topics: Introduction to SQL for BigQuery and Cloud SQL Rent-a-VM to Process Earthquake Data Weather Data in BigQuery Distributed Image Processing in Cloud Dataproc Analyzing Natality Data Using Vertex AI and BigQuery Predict Baby Weight with TensorFlow on AI Platform 🆓 Free Online Course ⏰ Duration : More than 6 hour 🏃‍♂️ Self paced ✅ Certification available Course Link #data #processing #data_science ➖➖➖➖➖➖➖➖➖➖➖➖➖➖ 👉Join @bigdataspecialist for more👈

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ETL vs REVERSE ETL vs ELT
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