Empowered by Python - A success story
summary
Company-wide migration to Python delivers concrete results: prototypes become saleable MVPs, tooling moves from MATLAB to Anaconda/Conda packaging, containerized deployment with Docker and Jupyter notebooks supports interactive visualization of 13.5 million points via Datashader, backed by a four petabyte Isilon cluster. The stack mixes Python data libs (numpy pandas scikit-learn matplotlib) with C++ for speed, uses Qt for GUIs, and amounts to 1.5 million lines of production Python that actually runs in the field.
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chapters (21)
- 0:00Intro
- 0:42INTRODUCING THE ROSEN GROUP
- 1:40TOOLS USED FOR PIPELINE INSPECTION
- 2:41RESEARCH & DEVELOPMENT
- 3:03EMPOWERED BY TECHNOLOGY
- 3:33ROSEN & PYTHON
- 4:25BIG DATA IN A NUTSHELL
- 6:25RUN LAB MEASUREMENTS
- 7:47RAPID PROTOTYPING OF IDEAS
- 9:03BIG DATA APPLICATIONS & STORAGE
- 9:30ROSEN & DATA SCIENCE
- 10:21CHALLENGES IN MACHINE LEARNING
- 10:59SMART WAYS TO FILL GAPS
- 11:32IMPROVED TESTING
- 12:29WE TAKE PYTHON & DATA SCIENCE SERIOUSLY
- 13:01HISTORICAL DEVELOPMENT
- 15:27CURRENT DEVELOPMENT
- 18:03FUTURE DEVELOPMENT
- 18:44INFRASTRUCTURE
- 21:43LOOKING FOR A COOL JOB? WE NEED YOU!
- 22:08MESSAGE TO TAKE HOME THE ZEN OF A HIDDEN CHAMPION
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