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Udemy - Python Data Science with the TCLab

seeders: 4
leechers: 5
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Added 4 years ago by freecoursewb in Other
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Udemy - Python Data Science with the TCLab (Size: 1.8 GB)
  001 Data Science Python Course.mp4 82.3 MB
  001 Data Science Python Course_en.srt 11.6 KB
  001 Install and Overview (Module 1).mp4 140.3 MB
  001 Install and Overview (Module 1)_en.srt 22.8 KB
  001 Interpolation (Module 9).mp4 126.5 MB
  001 Interpolation (Module 9)_en.srt 23.2 KB
  001 Prepare Data (Module 5).mp4 147.7 MB
  001 Prepare Data (Module 5)_en.srt 26.8 KB
  002 Import and Export Data (Module 2).mp4 145.7 MB
  002 Import and Export Data (Module 2)_en.srt 21.7 KB
  002 Install Python and Data Science Packages.html 1.3 KB
  002 Regression (Module 6).mp4 208.2 MB
  002 Regression (Module 6)_en.srt 36.6 KB
  002 Solve Equations (Module 10).mp4 220.7 MB
  002 Solve Equations (Module 10)_en.srt 38.2 KB
  003 Differential Equations (Module 11).mp4 99.8 MB
  003 Differential Equations (Module 11)_en.srt 17.5 KB
  003 Features (Module 7).mp4 152.4 MB
  003 Features (Module 7)_en.srt 27.8 KB
  003 Summarize with Statistics (Module 3).mp4 102.8 MB
  003 Summarize with Statistics (Module 3)_en.srt 13.9 KB
  004 Classification (Module 8).mp4 128.6 MB
  004 Classification (Module 8)_en.srt 19.5 KB
  004 Time Series (Module 12).mp4 93.3 MB
  004 Time Series (Module 12)_en.srt 13.6 KB
  004 Visualize Data (Module 4).mp4 181 MB
  004 Visualize Data (Module 4)_en.srt 31.6 KB
  Bonus Resources.txt 409.6 B
  Get Bonus Downloads Here.url 204.8 B
  external-assets-links.txt 204.8 B
  ▲ 30 total files

Description


Python Data Science with the TCLab
https://DevCourseWeb.com

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 14 lectures (4h 23m) | Size: 1.71 GB

Data science introduction for scientists and engineers

What you'll learn
Visualize data to understand relationships and assess data quality
Understand the differences between classification, regression, and clustering and when each can be applied
Detect overfitting and implement strategies to improve prediction
Understand engineering and business objectives to plan applications
Implement data science techniques successfully to complete a project

Requirements
Beginner Python experience is needed.
Consider the freely available course found on GitHub: APMonitor/begin_python to gain foundational experience with variables, loops, functions, lists, and other Python introductory topics.

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