» Andrew Tait

Andrew Tait is the founder and Chief Technology Officer of Decision Mechanics, a software and consulting firm specializing in the creative use of technology to improve organizational decision-making.

Andrew has designed commercial, off-the-shelf, solutions for strategic planning, performance improvement, and conflict management. His work in this area has led to numerous consulting and training relationships with major commercial and government organizations.

Throughout his career, Andrew has specialised in blending decision science, data analysis, and software development to deliver solutions to his clients. At present, he is focused on delivering web and mobile solutions, using technologies such as:

ASP.NET MVP

JavaScript

Xamarin

Swift

Prior to forming Decision Mechanics, Andrew held various commercial (technology consulting), government (defence) and academic (business) positions in the UK and US.

Andrew has taught for Learning Tree International since 2010 and specializes in the Big Data, .NET, Mobile & Web Development curriculums. He is also the technical editor of one of our new Big Data courses—Introduction to Data Science for Big Data Analytics.

Defining the Data Puzzle: Data Science vs. Big Data vs. Data Analytics & More

apr 4, 2019

Andrew Tait

I, like many others, am constantly frustrated by the sensationalist use of terminology in data science. Twitter user @xaprb neatly summed up my own feelings when he tweeted When you’re fundraising, it’s AI [Artificial Intelligence]. When you’re hiring, it’s ML [Machine Learning]. When you’re implementing, it’s linear regression. When you’re debugging, it’s printf(). As someone […]

Big Data & Data Science

Clustering data using k-means in ML.NET

aug 7, 2018

Andrew Tait

Microsoft recently released a preview of a machine learning framework for .NET developers—ML.NET. I needed to perform a clustering analysis from existing data in one of my applications. This is a pretty common machine learning task, so I decided to document the basic approach in this article. We’ll use the well-worn iris data set from […]

.NET/Visual Studio, Big Data & Data Science

.NET Core, .NET/Visual Studio, cluster analysis, code, data science, GitHub, k-means, machine learning, ML.NET

ML.NET—an open source, cross-platform, machine learning framework for .NET

jun 13, 2018

Andrew Tait

One of the products Microsoft introduced at their 2018 Build conference was an open source, cross-platform machine learning framework for .NET developers. ML.NET will …allow .NET developers to develop their own models and infuse custom ML into their applications without prior expertise in developing or tuning machine learning models. Democratisation of machine learning—-i.e. enabling people […]

.NET/Visual Studio, Big Data & Data Science

.NET/Visual Studio, boosted trees, framework, k-means, Logistic Regression, machine learning, naive bayes, pipeline, random forest, visual studio

Making sense of React’s different component styles

jan 17, 2018

Andrew Tait

React is an unopinionated framework. It gives you a lot of flexibility to do things your own way. This flexibility can be empowering once you are familiar with the framework, but it can make it a little daunting to get started. Every piece of code you see seems to be doing things in a slightly […]

Web Development

best practice, component, createClass, ES6, functional, React, Reactjs, stateless

Biometrics — Can You Afford to Lose a Finger?

jul 12, 2017

Andrew Tait

Biometric authentication has been attracting a lot of attention recently. Every day you see people deftly swiping their thumbs over their phones to unlock them using fingerprint recognition. Iris scanning technology is being introduced to India’s national biometric ID system. It’s the largest such system in the world—with over a billion users—and is used to […]

Cyber Security

authentication, biometric authentication, biometric security, biometric technology, biometrics, cyber security, facial recognition, fingerprint recognition, fingerprints, iris scanning, password

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