Oracle Magazine, July/August 2019
DEVELOPER PRODUCTIVITY ORACLE MAGAZINE JULY AUGUST 2019 18 of Oracle SQL Developer Data Modeler for Database Design Mastery Oracle Press 2015 focuses on big data when thinking about ML She tells a story of visiting a company and seeing its systems shutting down with no explanation Helping it discover why this was happening was a simple question of analyzing temperature data with ML she says which discovered that on the rare occasion when a certain door was left open the cold air would kill a particular machine and cause a cascading outage ML is not for answering if else questions she says Machine learning is for something you have no way to predict yourself ML is I have no idea what might happen but whatever happens I need to be prepared The world is changing so I will adapt to that HOW TO GET STARTED Understanding the plethora of ML terminology is the first step Helskyaho says noting that her popular presentations explain what these words mean and how they relate to each other You start out very confused because people are using different words with the same meaning and that can sometimes mislead you If you are a developer like me the next step is choosing the programming language you want to start with because theres no point to starting with all of them Use skills you already have and add something new she says Although Python is probably the most common language for working with ML if youve been using R SQL C Java start with that Next ask about algorithms models and how to prepare the data I think 80 of ML work is preparing the data because the data is usually not the best quality Helskyaho says Using a drag and drop tool such as Oracle SQL Developer enables you to build a realworld model and experiment with neural networks regression anomaly detection and classification algorithms Starter projects might be trying to What computers cannot do is understand the world Heli Helskyaho Community Ambassador
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