K-Nearest Neighbors (KNN) clustering is an unsupervised machine learning algorithm that can be used to classify data points based on their similarity to other points in the dataset. It is a simple yet effective method for grouping data into clusters, or “neighbourhoods,” based on the distance between points in feature space.

Are you someone who has zero financial background and has no idea what the Markowitz mean variance optimization model is all about? Don’t worry, you’re in the right place! This model might sound intimidating and complex, but it’s actually a pretty simple concept.

As a marketer, you know the importance of using data to drive your marketing strategy. By collecting and analysing data, you can better understand your target audience, identify opportunities for growth, and optimize your marketing efforts to achieve better results. One way to do this is by using regression analysis, a statistical technique that can help you understand the relationship between different variables and make predictions about future outcomes.

So, what is logistic regression and how does it work? In a nutshell, logistic regression is a way to predict the likelihood of a certain event occurring. For example, you might use logistic regression to predict the likelihood that a customer will make a purchase based on their past behaviour, or to predict the likelihood that a patient will develop a certain disease based on their medical history.

Customer segmentation is the process of determining the different customer groups that exist in a market with the aim of defining the group characteristics and thereafter determining the points of potential growth within the segments that will lead to increased market share[3,4,7].

In graphic design, a pull quote (also known as a lift-out pull quote) is a key phrase, quotation, or excerpt that has been pulled from an article and used as a page layout graphic element, serving to entice readers into the article or to highlight a key topic.