Tag Archives: Machine Learning

There’s no doubt that the test automation space is undergoing transformation. Machine Learning (ML), Deep Learning and Artificial Intelligence (AI) are being leveraged more and more as part of the test authoring and test analysis. While the space is still growing from a maturity stand-point, it is a great time for practitioners (developers and test engineers) to start understanding the ...

Telling the computer what to do is fun, but have you ever wondered how you can simply tell the computer one thing and it extends to another thing? I mean allowing the computer to make future executions without having to wait for exclusive commands from the programmer. Oh yeah, allowing the computer to indirectly make inference without waiting for input ...

We keep hearing about new solutions for test automation and continuous testing. Such solutions aim to increase the test automation authoring as well as the maintenance associated with these tests as the product evolves. With this trend, many software quality engineers, SDET, and test automation architects are asking themselves whether their job is at risk, and what’s the future holds ...

In today’s competitive and complex market, it is tough to develop a proper forecasting model for fulfilling demand in the supply chain process. Most of the prediction techniques deliver unsatisfied outcomes. The main reason for this disappointment is the old technique used in such operations. These models are not designed to perceive continuous information from available data to make decisions. ...

Before we begin, let’s get definitions straight — what is artificial intelligence (AI)? Or more specifically, what isn’t it? As you might expect, ask any technical person for a definition of something, and you’ll get a dozen different responses, and at least half of them will be, “It depends.” In my humble opinion, AI is a machine or program that ...

Welcome to the second part of the tutorial for scoring your PMML files using  LightningScorer, which is a side project of mine. Let’s find out how additional parameters work. The initial steps are similar to the first part of the tutorial. Get your local copy first git clone https://github.com/sezinkarli/lightningscorer.git and build it with maven mvn clean install and start it ...

You searched for some way to export your machine learning models so you can use them for evaluating your data and you see that you can export them in PMML format. You actually work in Java ecosystem but not motivated to write neither your PMML library nor an rest api for it. Then I will recommend you LightningScorer, which is ...

This project explores how to apply Machine Learning to IoT. In more details, as IoT platform, we will use Android Things and as Machine Learning engine we will use Google TensorFlow. Nowadays, Machine Learning is with Internet of Things one of the most interesting technological topics.  To give a simple definition of the Machine Learning, it is possible to the Wikipedia definition: ...

At OOP 2018 conference in Munich, I presented an updated version of my talk about building scalable, mission-critical microservices with the Apache Kafka ecosystem and Deep Learning frameworks like TensorFlow, DeepLearning4J or H2O. I want to share the updated slide deck and discuss a few updates about newest trends, which I incorporated into the talk. The main story is the ...