Commit f8599148 authored by Carp's avatar Carp

changes from 1note

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data scientists have a lot on their plate.
division of labor
in this book we will oversimplify the issues into "issues of data acquisition" and "issues relevnt to a data scientist".
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The  profvis  package is a powerful tool for line profiling in R. This package is provided by  the RStudio team, and its most appreciated feature is the interactive report that is automatically produced, representing a really effective way of visualizing and investigating time resources  requested by each part of your code.
Technical Foundations of Informatics:
Understanding SQL R Services: Understanding SQL R Services What Every SQL Professional Should Know
Intro to MSFT R Server:
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editions, etc
SQL Server R Services : Integrates R into SQL Server’s  database engine natively. ScaleR is available in Enterprise Edition only though. 
Microsoft R Open
In 2016, Microsoft bought Revolution Analytics, which is built around R and provides both an open source (Revolution R Open) and commercial (Revolution R Enterprise) development platform for R. Hea
Note that the very bottom option is something new. It says New R Server (Standalone) installation. You would select this option if you only wanted to install R Server as either a server (standalone, self-contained data analysis server, in other words) or a client (manipulating data from a remote SQL Server R Services installation). Note that you need the SQL Server 2016 services running as well, so this would be to add R services to an existing SQL Server 2016 installation.
Do you see that? Twenty new user accounts were created during installation and each of them are specifically created to interact with R Services. These 20 accounts are added to a new Group called SQLRUserGroup<instance_ name>, where <instance_name> is the name of your instance. So in my case, my group is named SQLRUserGroupSQL2016RS. If you followed this naming convention, yours will be named that as well.
The way that this is configured, we can work just fine from this server. We don’t need to define anything else or add any other user accounts, since we have already verified that R is working correctly in the database. Microsoft has some pretty good articles about how to configure the database instance to accept R scripts from external developers, which essentially entails adding the SQLRUserGroupSQL2016RS group as a new login in SQL Server. That way, when a user connects to the database instance to run R scripts, one of those 20 new user accounts is used to execute the script through the Launchpad service on behalf of the user. Microsoft has dubbed this implied authentication, since a user in the group would then be able to access SQL Server R Services remote
installing a new R pkg:
performing in-database predictions:
awesome demo and deck:
editable office documents from R:
What r packages are installed:
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docker sql with python:
python vs R
multipurpose langue vs designed for statisticians and data scientists
python is easier to learn, generally for OOP and procedural lang coders. data scientists without much development engineering experience.
R visualization is a bit more polished. R is very slow, wasn't built with scale and bigger datasets in mind.
learning paths:
installing external R packages:
ingest a web page:
70-773: R cert:
Microsoft 70-774, Perform Cloud Data Science with Azure Machine Learning
Parallel foreach looping:
Publish an R function as a stored proc:
consuming aml from sqlr:
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