Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

June 11, 2012

Machine Learning in Java has never been easier! [Java App <-> BigML Rest API]

Filed under: Java,Machine Learning — Patrick Durusau @ 4:25 pm

Machine Learning in Java has never been easier!

From the post:

Java is by far one of the most popular programming languages. It’s on the top of the TIOBE index and thousands of the most robust, secure, and scalable backends have been built in Java. In addition, there are many wonderful libraries available that can help accelerate your project enormously. For example, most of BigML’s backend is developed in Clojure which runs on top of the Java Virtual Machine. And don’t forget the ever-growing Android market, with 850K new devices activated each day!

There are number of machine learning Java libraries available to help build smart data-driven applications. Weka is one of the more popular options. In fact, some of BigML’s team members were Weka users as far back as the late 90s. We even used it as part of the first BigML backend prototype in early 2011. Apache Mahout is another great Java library if you want to deal with bigger amounts of data. However in both cases you cannot avoid “the fun of running servers, installing packages, writing MapReduce jobs, and generally behaving like IT ops folks“. In addition you need to be concerned with selecting and parametrizing the best algorithm to learn from your data as well as finding a way to activate and integrate the model that you generate into your application.

Thus we are thrilled to announce the availability of the first Open Source Java library that easily connects any Java application with the BigML REST API. It has been developed by Javi Garcia, an old friend of ours. A few of the BigML team members have been lucky enough to work with Javi in two other companies in the past.

With this new library, in just a few lines of code you can create a predictive model and generate predictions for any application domain. From finding the best price for a new product to forecasting sales, creating recommendations, diagnosing malfunctions, or detecting anomalies.

It won’t be as easy as “…in just a few lines of code…” but it will, what’s the term, modularize the building of machine learning applications. Someone has to run/maintain the servers, do security patches, backups but it doesn’t have to be you.

Specialization, that’s the other term. So that team members can be really good at what they do, as opposed to sorta good at a number of things.

If you need a common example, consider documentation, most of which is written by developers when they can spare the time. Reads like it. Costs your clients time and money trying to get their developers to work with poor documentation.

Not to mention costing you time and money when the software is not longer totally familiar to one person.

PS: As of today, June 11, 2012, Java is now #2 and C is #1 on the TIOBE list.

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