Linkedin - Python Data Analytics - From Notebooks to Production

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139.26 MB | 00:05:13 | mp4 | 1152X720  | 1.6:1
Genre:eLearning |Language:English

Files Included :
01 - Notebooks to production  (2.65 MB)
02 - What you should know  (1.47 MB)
03 - Using GitHub Codespaces  (1.93 MB)
01 - Understanding production  (5.12 MB)
02 - Where notebooks excel  (3.12 MB)
03 - Where notebooks come short  (4.57 MB)
01 - Why you should organize your code  (2.41 MB)
02 - Module API  (12.39 MB)
03 - Sub modules  (2.91 MB)
04 - Main  (3.65 MB)
05 - Challenge Convert logs notebook  (1.25 MB)
06 - Solution Convert logs notebook  (2.22 MB)
01 - Why testing is important  (4.81 MB)
02 - Running notebooks  (6.97 MB)
03 - Parametrized tests  (3.71 MB)
04 - Test fixtures  (5.22 MB)
05 - Continuous integration  (4.5 MB)
06 - Challenge Test tags  (2.09 MB)
07 - Solution Test tags  (3.53 MB)
01 - The problems with dependencies  (7.09 MB)
02 - Specifying and installing dependencies  (6.74 MB)
03 - Separating test dependencies  (4.11 MB)
04 - Distributing your package  (10.51 MB)
05 - Challenge Create an environment  (2.2 MB)
06 - Solution Create an environment  (2.55 MB)
01 - Logging and metrics  (4.27 MB)
02 - Configuration  (3.78 MB)
03 - Performance tuning  (11.9 MB)
04 - Securing your code  (5.53 MB)
05 - Challenge Make the monthly report production ready  (1.33 MB)
06 - Solution Make the monthly report production ready  (2.92 MB)
01 - What's next  (1.71 MB)

Screenshot

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