Machine learning for Java developers

Self-driving cars, face detection software, and voice controlled speakers all are built on machine learning technologies and frameworks–and these are just the first wave. Over the next decade, a new generation of products will transform our world, initiating new approaches to software development and the applications and products that we create and use.

As a Java developer, you want to get ahead of this curve now–when tech companies are beginning to seriously invest in machine learning. What you learn today, you can build on over the next five years, but you have to start somewhere.

This article will get you started. You will begin with a first impression of how machine learning works, followed by a short guide to implementing and training a machine learning algorithm. After studying the internals of the learning algorithm and features that you can use to train, score, and select the best-fitting prediction function, you’ll get an overview of using a JVM framework, Weka, to build machine learning solutions. This article focuses on supervised machine learning, which is the most common approach to developing intelligent applications.

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Serverless computing with AWS Lambda

Serverless computing may be the hottest thing in cloud computing today, but what, exactly, is it? In this two-part article you’ll get started with serverless computing–from what it is, to why it’s considered disruptive to traditional cloud computing, and how you might find yourself using it in Java-based programming. Following the overview, you’ll get a tutorial introduction to AWS Lambda, which is considered by many the premiere Java-based solution for serverless computing today. In Part 1, you’ll use AWS Lambda to build your first serverless function in Java. In Part 2, you’ll integrate your Lambda functions with DynamoDB, then use the AWS SDK to invoke Lambda functions in a Java application.

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21 rules for faster SQL queries

Everyone wants faster database queries, and both SQL developers and DBAs can turn to many time-tested methods to achieve that goal. Unfortunately, no single method is foolproof or ironclad. But even if there is no right answer to tuning every query, there are plenty of proven do’s and don’ts to help light the way. While some are RDBMS-specific, most of these tips apply to any relational database.

Whether you’re coding on SQL Server, Oracle, DB2, Sybase, MySQL, or some other relational platform, your goal is the same: You want the database to support as many concurrent users as practical while processing queries as quickly as it can. That means you need to minimize locking, I/O, and network traffic, while optimizing space and resource management. 

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