现已上线！2025 年 Telegram 研究 — 年度关键洞察 
Data Science & Machine Learning
前往频道在 Telegram
Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free For collaborations: @love_data
显示更多📈 Telegram 频道 Data Science & Machine Learning 的分析概览
频道 Data Science & Machine Learning (@datasciencefun) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 75 933 名订阅者，在 教育 类别中位列第 2 103，并在 印度 地区排名第 4 204 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 75 933 名订阅者。
根据 23 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 731，过去 24 小时变化为 33，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 2.95%。内容发布后 24 小时内通常能获得 0.86% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 2 239 次浏览，首日通常累积 650 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 learning, accuracy, distribution, panda, dataset 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：
“Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free
For collaborations: @love_data”
凭借高频更新（最新数据采集于 24 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。
75 933
订阅者
+3324 小时
+587 天
+73130 天
帖子存档
Deep Learning with Tensorflow videos
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Some of the essential libraries of Python that are used in Data Science
Numpy
SciPy
Pandas
Matplotlib
Keras
TensorFlow
Scikit-learn
Which of the following are important skills for a data scientist?
Who is Data Scientist?
He/she is responsible for collecting, analyzing and interpreting the results, through a large amount of data. This process is used to take an important decision for the business, which can affect the growth and help to face compititon in the market.
A data scientist analyzes data to extract actionable insight from it. More specifically, a data scientist:
Determines correct datasets and variables.
Identifies the most challenging data-analytics problems.
Collects large sets of data- structured and unstructured, from different sources.
Cleans and validates data ensuring accuracy, completeness, and uniformity.
Builds and applies models and algorithms to mine stores of big data.
Analyzes data to recognize patterns and trends.
Interprets data to find solutions.
Communicates findings to stakeholders using tools like visualization.
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