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Train ML Models With SQL You Already Know
BigQuery automates data prep, analysis, and predictions with built-in AI assistance.
Build and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
Scale your Pandas workflows by changing a single line of code
...It is not necessary to know in advance the available hardware resources in order to use Modin. Additionally, it is not necessary to specify how to distribute or place data. Modin acts as a drop-in replacement for pandas, which means that you can continue using your previous pandas notebooks, unchanged, while experiencing a considerable speedup thanks to Modin, even on a single machine. Once you’ve changed your import statement, you’re ready to use Modin just like you would pandas.
osDQ dedicated to create apache spark based data pipeline using JSON
This is an offshoot project of open source data quality (osDQ) project https://sourceforge.net/projects/dataquality/
This sub project will create apache spark based data pipeline where JSON based metadata (file) will be used to run data processing , data pipeline , data quality and data preparation and data modeling features for big data. This uses java API of apache spark. It can run in local mode also.
Get json example at https://github.com/arrahtech/osdq-spark
How to...
...The IDE is focused around the concept of Visual-, Online-, Data-Centric-, Concurrent-, and Runtime- Code, whilst remaining an IDE to handle OASIS Programming. The IDE has a number of visual code drag and drop features. The Tool is by no means a representative of the Cyclical UML Model- and Code concept, but rather a replacement. The IDE Tool is focused around (Team Based) System Engineering, Meta Programming, Visual Coding, Concurrent Processing and, Databases and Big Data.