## Supervised vs Unsupervised Learning, Explained

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

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

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

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

A few weeks ago, an acquaintance told me that he was interested in getting started with machine learning. He’s a web developer who primarily works in Ruby and Python, but also has a small amount of experience with R. Day-to-day, his work is run-of-the-mill web development, and he’s confessed to me that he’s a bit … 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

## A quick introduction to machine learning in R with caret

If you’ve been using R for a while, and you’ve been working with basic data visualization and data exploration techniques, the next logical step is to start learning some machine learning. To help you begin learning about machine learning in R, I’m going to introduce you to an R package: the caret package. We’ll build … Read more