Launching machine learning locally. Should I be using a local Datalab or Jupyter instance?
I am doing some machine learning and data analysis based on data from Google Analytics and other sources.
I was able to install Cloud Datalab locally and connect to my BigQuery, however I'm not sure if this is the best way to do things. I can see that with vanilla Jupyter notebooks with Pandas I can connect to BigQuery. Regular Jupyter has the advantage of running without Docker and also has Python 3.
So I'm wondering if there is any benefit to doing this with Cloud Datalab locally, other than highlighting the SQL syntax? In short, are all the benefits of Cloud Datalab only relevant to cloud computing, or does it offer any benefits over Jupyter for on-premises deployments?
Thank!
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Even if you are using regular Jupyter, you can also install the Python Datalab package to use most of the functionality of datalab.
My reasons for using Datalab over Jupyter when running locally:
- Running docker provides a well tested environment.
- PyDatalab offers API and BigQuery magic that makes a good BigQuery marketplace. google.datalab.bigquery offers more than just creating a dataframe from a query.
- Integration of BigQuery with graphics (%% chart can accept BQ queries).
- Machine learning tools and MLToolbox.
- Various user interfaces.
Jupyter + Datalab package gives you 2, 3 and 4.
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