The 2 Data Science Topics Every CEO Should Care About

This blog is taken as an excerpt from the Learning Tree eBook, Building Your Data Science Dream Team. Click here to access the full eBook › Many executives today know that data science is important, but they’re not sure where to start, or which projects to start advocating for on the ground level of a […]
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Defining the Data Puzzle: Data Science vs. Big Data vs. Data Analytics & More

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 […]
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Clustering data using k-means in ML.NET

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

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 […]
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Making sense of React’s different component styles

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 […]
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