Subject archive for "code," page 2

In this article, we will introduce and implement k-nearest neighbours (KNN) as one of the supervised machine learning algorithms. KNN is utilised to solve classification and regression problems. We will provide sufficient background and demonstrate the utility of KNN in solving a classification problem in Python using a freely available dataset.

In this blog post we give a quick introduction to Ray. We talk about the architecture and execution model, and present some of Ray's core paradigms such as remote functions and actors.

Data is all around us, from the spreadsheets we analyse on a daily basis, to the weather forecast we rely on every morning or the webpages we read. In many cases, the data we consume is simply given to us, and a simple glance is enough to make a decision. For example, knowing that the chance of rain today is 75% all day makes me take my umbrella with me. In many other cases, the data provided is so rich that we need to roll up our sleeves and we may use some exploratory analysis to get our heads around it. We have talked about some useful packages to do this exploration in a previous post.

We all have heard how data is the new oil. I always say that if that is the case, we need to go through some refinement process before that raw oil is converted into useful products. For data, this refinement includes doing some cleaning and manipulations that provide a better understanding of the information that we are dealing with.