idomi

7 ms·

31.
by idomi 5y ago
Or Ploomber?
32.
by idomi 5y ago
Pretty strong accusation, are you sure re-data isn't "inspired" from Monte Carlo? :)
33.
by idomi 5y ago
Great job Elementary team! Does this in essence similar to the aws deeque project but fancier and more inclusive of edge cases, common scenarios? ( https://github.com/awslabs/deequ )
34.
by idomi 5y ago
Great piece! I've seen tons of data scientists that move from notebooks into .py scripts, usually it's an org decision. I don't see the point in writing the same code twice.
35.
by idomi 5y ago
Not really, data scientists love notebooks, it's pretty inefficient to move out of the notebooks.
36.
by idomi 5y ago
Well written. I think that airflow is being enforced in organizations as the main orchestrator even though it's not always the right too for the job. In addition, organizations has to enforce a micro-services approach to have modular c
37.
by idomi 5y ago
Thanks for letting us know! So the audio is ok on laptops and mobiles. On the video you're right, it's a bug we need to fix since it's within an iframe you can't expand it into full screen mode.
38.
by idomi 5y ago
We took an approach of keeping the notebook interface/IDE, and behind the scenes Ploomber converts it into .py files so you can collaborate with teammates through Git. The users can still open those as a notebook and interact with the
39.
by idomi 5y ago
I believe essentially all of the tools mentioned here are focusing on the engineering persona and not the Data Scientist. Writing classes and functions isn't the jargon of a Data Scientist. At Ploomber we tried to put the Data Scientis
40.
by idomi 5y ago
We've built the Ploomber to work with R as well comparing to others who believe only python is for ML. Ploomber is an open source tool that can integrate with R and R studio out of the box. Check it out! https://github.com&#
41.
by idomi 5y ago
We've built the Ploomber open source tool for that exact reason - true open source! We've been trying to focus on the data scientists, not taking them out of jupyter and definitely making sure they can execute what they want witho
42.
by idomi 5y ago
This is a great insight! I think parameterizing the notebooks is part of the solution, moving to production shouldn't be time-consuming and definitely no need to refactor the code like I've seen some people do. I'd love to ge
43.
by idomi 5y ago
We actually took some of the best of both world, interactivity via Jupyter and the IDE strength, make sure to check out this: https://ploomber.io/blog/vscode-pycharm/