Linkedin - Python Data Analytics - From Notebooks to Production
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)
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