Predictive modelling with Python
summary
Covers predictive modeling using Python tools for data analysis, focusing on practical workflows and libraries (slides linked). Discusses applying Python ecosystems—likely including packages shown in slides and accompanying GitHub repo—to manage, process and analyze data for building predictive models.
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chapters (10)
- 0:00Start
- 0:44Big RAM is eating big data
- 14:21The need for scaling out in ML
- 17:13Limitations of PySpark
- 46:21Massively Parallel Processing
- 46:44Problem with the use of SQL in MPP
- 49:19Secrets of the success of Python (& R) in Data Science
- 50:02Conclusion
- 51:46Dask + Distributed limitations
- 54:41dask/distributed on GKE
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