Developers and data scientists often work together in teams, but our objectives and approaches to data and ML couldn’t be more different: from how we reason about data, why we collect it, and the tools we use, to where AI actually fits in our workflow.
In this Ask the Expert event, you will be able to chat with Zan and ask your questions about AI and ML development, DataRobot APIs, etc. On this interesting and important topic, Zan is available to answer your questions.
|Zan Markan is a Developer Advocate at DataRobot. He has spent over a decade working in technology, in a variety of roles and enterprises—as a developer, manager, and in developer relations.
He is passionate about educating developers and enabling them to be successful with whichever technology they are using.
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I've had some exposure to TensorFlow and PyTorch through research for different ml projects and discussions with my colleagues. How does DataRobot differ from them?
We are working on a set of demos and example projects. I'll be publishing the first one very soon - in the next few days.
I will update this response when I will have posted it and let you know!
To my knowledge most things in the DataRobot UI are supported with APIs and libraries and vice versa, but there might be a few minor discrepancies with features not available in the APIs and libraries yet.
We don’t have a list to share, but if you have a concrete example in mind then our support team will be able to answer you this.
Hi @ErnieZ, thank you for your question.
The most challenging thing when working with ML and AI as a developer to me is the step of gathering and preparing data for training - what will later produce our ML model.
A training dataset requires a column designated as the target - that is the value you want to predict, and is not the data that you will have at the time of making predictions.
Therefore, a training dataset might require you to combine multiple sources of data so it contains this target as well.
Other than that, it used to be that training the model itself was also a quite a time consuming process, but I find it pretty straightforward with DataRobot nowadays.
Hope this answers your question!
Thank you Zan this is wonderful!
A follow-up question, What is the hardest or most challenging thing when working with ML and AI as a developer?
Hi @nico1e. And thank you for your question.
It's really great that you asked about a dedicated developer section in the community, as we're just preparing to launch it.
Our plan is to create the best resource fo developers wishing to learn ML and AI skills and technologies, and adopt them into their toolsets, as well as to give the developer community the chance to influence our developer experience going forward.
We're still a few days away from launching it, but we've prepared a short questionnaire where you can register your interest, tell us what you would like to see, and we can notify you when it's available.
You can find the form at the following link.
Hope this helps!
This question came through before we opened it up - from Mladen:
From what I've seen DataRobot can definitely be used (and is being used) to solve pretty much any ML use-case out there. From finance to manufacturing, healthcare, retail, and everything in between. I found a pretty good overview here: https://www.datarobot.com/use-cases/
Would DataRobot be a good solution for more general ML, or would it perform well with practically every problem ML can solve?