Supervised vs Unsupervised Learning, Explained

An image that shows the difference between supervised and unsupervised learning.

In this article, I’ll explain supervised vs unsupervised learning. The tutorial will start by discussing some foundational concepts and then it will explain supervised and unsupervised learning separately, in more detail. If you need something specific, just click on the link. The following links will take you to specific sections of the article. Table of … Read more

How to do linear regression in R

A visualization of an example linear regression in R, performed using ggplot2.

Linear regression. It’s a technique that almost every data scientist needs to know. Although machine learning and artificial intelligence have developed much more sophisticated techniques, linear regression is still a tried-and-true staple of data science ….

You don’t need to know much math for data science

A pen on a piece of paper with math equations

Recently, a Sharp Sight blog reader emailed me and asked for advice about data science prerequisites. He was nervous about math. Someone had told him that in order to study data science, he needed to learn a long list of math topics first: Precalculus Calculus Multi variable calculus Trigonometry Linear algebra Differential equations Statistics Although … Read more

Welcome to the Second Machine Age

second machine age analogy to first machine age

The world has just entered one of the biggest transitions in history. That’s the contention of two MIT economists, Eric Brynjolfsson and Andrew McAfee. In their recent book, The Second Machine Age, they argue that big data, computation, and innovation are changing our economy and institutions with a magnitude greater than almost anything ever seen … Read more

How to use data analysis for machine learning (example, part 1)

In my last article, I stated that for practitioners (as opposed to theorists), the real prerequisite for machine learning is data analysis, not math. One of the main reasons for making this statement, is that data scientists spend an inordinate amount of time on data analysis. The traditional statement is that data scientists “spend 80% … Read more

The real prerequisite for machine learning isn’t math, it’s data analysis

When beginners get started with machine learning, the inevitable question is “what are the prerequisites? What do I need to know to get started?” And once they start researching, beginners frequently find well-intentioned but disheartening advice, like the following: You need to master math. You need all of the following: – Calculus – Differential equations … Read more

What’s the difference between machine learning, statistics, and data mining?

Over the last few blog posts, I’ve discussed some of the basics of what machine learning is and why it’s important: – Why machine learning will reshape software engineering – What is the core task of machine learning – How to get started in machine learning in R Throughout those posts, I’ve been using the … Read more