julienkervizic

Yeah, knowledge of window functions allows to solve quite complex data manipulation problems fairly easily.

For some data-engineering type of work such as sessionization, doing it without window functions would make the task really complicated.

In some platforms such as MySQL there are alternatives such as correlated subqueries that also allow to do extensive data manipulation easily, but at quite the cost penalty.

In my experience, people who know window functions, are already quite well versed in SQL and thus can serve as a good proxy to gauge overall experience in Analytical SQL.

Yes it covers a bit more than what people tend to see in Machine Learning which is the model training part. From the code base it looks to cover:

1) feature preparation and model training as part of notebooks

2) Creation of a Flask API to interact with the trained models. This includes feature enrichment based on APIs input, so as to match the expected inputs by the model

3) Creation of an UI to interact with the API/Model

4) Setup of NGinx and docker to surface that application

Each part is covered in a minimal manner compared to most enterprise data products, and only cover 1 of the approach for end to end ML, but I think it does the job well to demonstrate the scope of work that is needed to put ML data products into production, and could be used as good introduction.

They got purchased by Alteryx

Yeah IN/ Not IN should be able to use index/hash scan when given normal values. I am under the impression from the note though that this is related to subqueries fitting in a IN/NOT IN clause, eg: SELECT * FROM tableA IN (SELECT * FROM tableB)

Any reason why you took the approach of mounting a share drive rather than push to a cloud storage solution? s3 or other? And not used a more "cloud based" container solution like Kubernetes, Azure Container instance.. ?

Neat, definitely something I would want to give a try.

I see though that it only supports pure python for building packages, does that mean that it doesn't build if you are dependent on compiled libraries?

Is there also a plan to add some of the functionality of bundling tools such as web-pack into this build phase? like automated css optimization, image compression... Could be handy for some django/flask projects.

great idea, definitely seems like something I would use.