Accelerate your machine learning workflow


By Peter Jeffcock, Senior Principal Product Advertising and marketing Director – Massive Information

There are many totally different concepts in regards to the optimum machine learning workflow and even precisely what number of steps there are. However no matter what number of totally different steps there are, we are able to all agree that there’s rather a lot concerned in getting from a good suggestion, to a having a machine studying mannequin in manufacturing and delivering worth. So, any option to shorten that data science journey is value investigating. I need to present you ways precisely how we are able to shorten that journey utilizing Oracle Cloud Infrastructure Data Science, and let you understand how to test it and trial it for your self.

We’ve taken an extended have a look at the machine studying workflow and located a number of areas the place we are able to automate duties which are tedious, time-consuming or complicated. Let’s have a look.

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Exploratory knowledge evaluation

Whenever you first get a brand new knowledge set, it’s worthwhile to spend a while exploring it and studying what’s in there, and the way it could be helpful. We add automation to that course of by producing summaries, visualizations and correlations that may take you a great distance in direction of understanding what that knowledge would possibly be capable of do for you.


Characteristic engineering

Even probably the most helpful knowledge set wants extra work. We offer really helpful transformations to the dataset and permit customers to choose and select which transformations to use to the dataset, so it’s prepared for mannequin coaching.   



Our AutoML is developed in collaboration with the Oracle Labs analysis crew.  It’s going to run quite a lot of experiments to make sure that you get the best algorithm, with the optimum hyper-parameter settings. And it does all this whereas evaluating mannequin efficiency to make sure the outcomes will probably be what you want.


Mannequin clarification

As soon as a mannequin is operating and producing outcomes or predictions, that anyone goes to ask: “Why did it give that outcome?” With world and native mannequin explainers, we are able to present you which ones attributes contributed to any given outcome, so you’ll be able to inform in case your mannequin is working as you count on. You’ll be able to even doubtlessly detect bias within the mannequin brought on by underlying bias within the unique knowledge – very helpful if a lawyer or regulator desires to make sure that there isn’t any discrimination occurring.


Automating all these features doesn’t simply save time (although in fact they do) or prevent from doing issues which are extra tedious than artistic (although it does that, too). For the reason that automation relies on greatest practices, it may get even consultants near an optimum method, permitting them to concentrate on the actually arduous stuff. And for non-experts, it may typically ship higher outcomes than they may do on their very own.

However don’t take my phrase for it. There’s a free hands-on lab that you may attempt for your self. We can even be operating an interactive office hours on October 9, 2020, to assist customers with any issues they could have with the lab. See if automation might help you speed up your workflow. 

To study extra about knowledge science, go to the Oracle Data Science web page, and observe us on Twitter @OracleDataSci


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