Machine Learning Archives

October 20, 2024 Machine Learning

AI – An Advanced Civilization or a One-Trick Pony

Oct 19, 2024 Author’s Note This article, unlike the others on this website, is not about how some AI algorithms work. Instead, it is a personal opinion on AI and the future of our world. My hope is to generate more discussions on AI from this perspective. In such an undertaking, it is likely that I have made mistakes and failed to consider some critical aspect of the whole picture. Please feel free to comment and help me learn more. After some false starts, we are witnessing the true dawn of Artificial Intelligence (AI) today. Many people, including high profile

June 6, 2022 Machine Learning

An Intuitive Guide to Linear Regression

We have described before how supervised learning can help us predict a continuous-valued output or organize the input into discrete categories, commonly known as regression and classification problems, respectively. In this article, we describe linear regression and leave the classification algorithms for a future post. What is Linear Regression? Suppose that you are a young investor living in a region with cold climate. One day an idea flashes in your mind that perhaps the shares in the regional stock market climb linearly with the temperature: the better the weather, the higher the prices. You already know what the temperature is

Regression and classification in supervised learning

May 16, 2022 Machine Learning

What is Supervised Learning?

In a previous article, we had a little introduction to the big picture of machine learning. More than what is it is, we focused on what it is not. Today we explore the category of supervised learning that opens the door to our understanding of advanced machine learning techniques. To see how supervised learning is proliferating in all walks of life, consider a few examples below. Insurance companies can predict the costs of storms damages for the future years due to climate change and adjust their premiums accordingly. During an interview, companies can classify the candidates with high and low

December 21, 2021 Machine Learning

A Beginner’s Guide to Bayesian Methodology

Thomas Bayes was an English statistician and Presbyterian minister who came up with this theorem in 18th century during his investigation on how to update the understanding of a phenomenon as more evidence becomes available. At that time, he did not deem it worthy of publication and never submitted it to any journal. It was discovered in his notes after his death and published by his friend Richard Price. In the past, Bayesian theorem was associated with highly complicated mathematics (and rightly so), and hence it was generally a topic of interest for mathematicians, statisticians and similar professionals. However, as

Buridan's donkey at an equal distance from hay and water

April 12, 2023 Machine Learning

k-Nearest Neighbors (k-NN) – A Man is Known by the Company He Keeps

Aesop was a Greek storyteller who created lots of short stories more than 2500 years ago (such as the hare and the tortoise), now collectively known as Aesop’s Fables. "A man is known by the company he keeps" is a quote also attributed to him that has survived through the ages and has proven to be a timeless truth. The k-Nearest Neighbors (k-NN) algorithm is essentially based on the same idea. It suggests that when a machine needs to classify a new data point in an application, examining its neighboring data points is an effective strategy. In the spirit of