现已上线！2025 年 Telegram 研究 — 年度关键洞察 
DataSpoof
前往频道在 Telegram
Learn Data Science https://dataspoof4081.graphy.com/membership Artificial Intelligence Machine Learning Data Science Deep learning Computer vision NLP Big data
显示更多📈 Telegram 频道 DataSpoof 的分析概览
频道 DataSpoof (@dataspoof) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 16 102 名订阅者，在 教育 类别中位列第 12 529，并在 印度 地区排名第 26 401 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 16 102 名订阅者。
根据 25 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 -159，过去 24 小时变化为 -12，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 7.31%。内容发布后 24 小时内通常能获得 2.29% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 0 次浏览，首日通常累积 369 次浏览。
- 互动与反馈： 受众积极参与，单帖平均反应数为 0。
- 主题关注点： 内容集中在 api, llm, pipeline, +9183182, engineer 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 Data Science
https://dataspoof4081.graphy.com/membership
Artificial Intelligence
Machine Learning
Data Science
Deep learning
Computer vision
NLP
Big data”
凭借高频更新（最新数据采集于 26 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。
16 102
订阅者
-1224 小时
-377 天
-15930 天
帖子存档
16 100
OpenAI codex cli a coding agent that can run on your terminal. complete video is here
https://youtu.be/TH8T-Dm0y8I?si=5QOVEwJHppv4p5a6
16 100
Complete text data preprocessing in python .
Do watch it, Like, comment and Subscribe to our YouTube channel for data science content like this.
https://youtu.be/z_MuPMRejJE?si=WteUoVt6Bl9C8c2e
16 100
Llama 4 is out beating the deepseekv3 model check out the more details
https://www.linkedin.com/posts/abhishek-kumar-singh-8a6326148_datascience-machinelearning-ai-activity-7314452968391561217-gGOa?utm_source=share&utm_medium=member_android&rcm=ACoAACOks34BFSi927IWily_2kgESJV38GQlIWQ
16 100
Master Python programming in 30 days
https://www.udemy.com/course/master-python-programming-in-30-days-2025/?couponCode=7E26C0F137E5723E1E63
16 100
Let's learn about Model Interpretability
Interpretability is essential for:
Model debugging - Why did my model make this mistake?
Feature Engineering - How can I improve my model
Detecting fairness issues - Does my model discriminate?
Human-AI cooperation - How can I understand and trust the model's decisions?
Regulatory compliance - Does my model satisfy legal requirements?
High-risk applications - Healthcare, finance, judicial,
16 100
+1
AutomatedCleaning is a Python library for automated data cleaning. It helps preprocess and analyze datasets by handling missing values, outliers, spelling corrections, and more
Features
Supports both large (100+ GB) and small datasets
Detects and handles missing values and duplicate records
Identifies and corrects spelling errors in categorical values
Detect outliers
Detects and fixes data imbalance
Identifies and corrects skewness in numerical data
Checks for correlation and detects multicollinearity
Analyzes cardinality in categorical columns
Identifies and cleans text columns
Detect JSON-type columns
Performs univariate, bivariate, and multivariate analysis
https://lnkd.in/gmaStAsp
16 100
How to create an End to End LLM application in aws
Do watch it, like and subscribe to our YouTube channel
https://youtu.be/-3Pk8KFPsB4?si=7l4An6RZGBZDowH5
16 100
+1
Feedback received for the Generative AI training from the students from University of texas
Dm us on whatsapp for real time training +9183182 38637
16 100
Agentic AI #2
How to create an AI agent using CrewAI
Do watch it, like and subscribe to our YouTube channel. More videos are coming
https://youtu.be/ikDJ56k0Y9U?si=UyUkuMXOTC8kPC0l
16 100
Agentic AI #1
How to Create a flight agents
Do watch it, like and subscribe to our YouTube channel. More videos are coming
https://youtu.be/ivt5q_pIeE4?si=7P1Z-9LHlQKlhttO
