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Data Science & Machine Learning

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

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📈 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 75 821 名订阅者,在 教育 类别中位列第 2 110,并在 印度 地区排名第 4 270

📊 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 75 821 名订阅者。

根据 19 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 855,过去 24 小时变化为 10,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 3.21%。内容发布后 24 小时内通常能获得 1.26% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 2 431 次浏览,首日通常累积 953 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 20 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。

75 821
订阅者
+1024 小时
+1447
+85530
帖子存档
"📊 Data Analysis Tip: Have you ever wondered how outliers can impact your analysis? Outliers are data points that significantly differ from the rest of your dataset. They can skew results and affect the accuracy of your insights. Tip: Before removing outliers, it's essential to understand their origin. Are they errors, natural variations, or something else? Removing or adjusting them without proper justification can lead to biased results.

Machine Learning with Python.pdf28.13 MB

Probability Distributions Cheat Sheet.pdf2.57 MB

Hands-On Graph Neural Networks Using Python.pdf35.45 MB

🔰 Learning Python for Data Analysis and Visualization ⏱ 21 Hours 📦 110 Lessons Learn python and how to use it to analyze,vi
🔰 Learning Python for Data Analysis and Visualization ⏱ 21 Hours 📦 110 Lessons Learn python and how to use it to analyze,visualize and present data. Includes tons of sample code and hours of video! Taught By: Jose Portilla Download Full Course: https://t.me/pythonanalyst/26 Download All Courses: https://t.me/DataAnalystInterview

Natural Language Processing with Transformers.pdf17.27 MB

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Python Automation Cookbook Jaime Buelta, 2020

Practical Statistics for Data Scientists.pdf15.98 MB

R for Data Science.pdf19.76 MB

1. What are the different subsets of SQL? Data Definition Language (DDL) – It allows you to perform various operations on the database such as CREATE, ALTER, and DELETE objects. Data Manipulation Language(DML) – It allows you to access and manipulate data. It helps you to insert, update, delete and retrieve data from the database. Data Control Language(DCL) – It allows you to control access to the database. Example – Grant, Revoke access permissions. 2. List the different types of relationships in SQL. There are different types of relations in the database: One-to-One – This is a connection between two tables in which each record in one table corresponds to the maximum of one record in the other. One-to-Many and Many-to-One – This is the most frequent connection, in which a record in one table is linked to several records in another. Many-to-Many – This is used when defining a relationship that requires several instances on each sides. Self-Referencing Relationships – When a table has to declare a connection with itself, this is the method to employ. 3. How to create empty tables with the same structure as another table? To create empty tables: Using the INTO operator to fetch the records of one table into a new table while setting a WHERE clause to false for all entries, it is possible to create empty tables with the same structure. As a result, SQL creates a new table with a duplicate structure to accept the fetched entries, but nothing is stored into the new table since the WHERE clause is active. 4. What is Normalization and what are the advantages of it? Normalization in SQL is the process of organizing data to avoid duplication and redundancy. Some of the advantages are: Better Database organization More Tables with smaller rows Efficient data access Greater Flexibility for Queries Quickly find the information Easier to implement Security

PYTHON_DATA_SCIENCE_ESSENTIALS_THIRD_EDITION @computer_books.pdf6.63 MB

Statistics Slam Dunk.pdf8.97 MB

Electrical Machine Fundamentals with Numerical Simulation using MATLAB/SIMULINK Atif Iqbal, 2021

Stack Overflow jumps into the generative AI world with OverflowAI

Natural Language Processing in the Real World.pdf25.62 MB

Friendly Introduction to Numerical Analysis Brian Bradie, 2006

Siemens is hiring Data Analyst/ Data Engineer! https://t.me/getjobss/1445

The Pragmatic Programmer for Machine Learning.pdf7.68 MB

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Python Programming Notes 📝