Understanding data: How statistics and machine learning learn from samples

There is an analogy in data science between inferential statistics and machine learning. Both fields aim to extract knowledge from limited data. Imagine wanting to understand the health of an entire forest. It’s impossible to examine every single tree. Instead, a researcher might take a random sample of trees and measure their height, trunk diameter,… Continue reading Understanding data: How statistics and machine learning learn from samples

Making Sense of Data: Unpacking Machine Learning Basics

Machine learning (ML) unlocks the potential of data by enabling computers to learn and perform tasks without explicit programming. Think of it as teaching computers through data, enabling them to make decisions or predictions. This article unpacks the basic concepts of ML. Data as Building Blocks Think of countless data points as the building blocks… Continue reading Making Sense of Data: Unpacking Machine Learning Basics

What would Leibniz think about ChatGPT?

What would Gottfried Wilhelm Leibniz, the 17th-century philosopher and mathematician, think of ChatGPT if he were alive today? How does his work relate to the technological revolution brought about by generative AI? Leibniz was captivated by the prospect of a universal language that could represent and manipulate human knowledge. In addition to this, he developed… Continue reading What would Leibniz think about ChatGPT?

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