Toolkits for Machine Learning

Just use one and stick to it

There are many toolkits available for doing typical data analysis/data mining/machine learning tasks. There are programming languages, libraries, frameworks and development environments to choose from. Some are aimed at solving particular problems, others at techniques and algorithms. This presents a challenge to all the newcomers. Which toolkits to learn? Just one? All of them? I’ve done the mistake of trying to use too many. I’ve been using R, Octave, Python and Matlab on and off. [Read More]

Applied Machine learning

From Calculus to Jupyter

I’m going to break another blogging taboo. Namely, I admit the prolonged silence. Somehow, talking about the blogging platform hasn’t killed this blog so, who knows, maybe this won’t either. I’ve been busy changing from one awesome job to another, which I’ll talk about in a separate post. From now on, though, I’ll keep posting once a week, rotating a few persistent themes: technology (software engineering and machine learning), sports (cycling, running, training), travel and personal reflections. To keep up I’ll give myself roughly 1 hour per week to get the post published. We’ll see how that goes…

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