Why should I read this, and what will I learn?

Machine learning is a field that threatens to both augment and undermine exactly what it means to be human, and it’s becoming increasingly important that you—yes, you—actually understand it.

I don’t think you should need to have a technical background to know what machine learning is or how it’s done. Too much of the discussion about this field is either too technical or too uninformed, and, through this blog, I hope to level the playing field.

This is for smart, ambitious people who want to know more about machine learning but who don’t care about the esoteric statistical and computational details underlying the field. You don’t need to know any math, statistics, or computer science to read and understand it.

By the end of this post, you’ll:

1. Understand the basic logical framework of ...

Lets say you have a dataset for binary classification. Each data point x has n-dimensions, and the target value is y = 1 or -1 for the two classes.

The perceptron

The perceptron algorithm can be visualized as follows.

For a given data point x, the prediction is simply b...

Deep learning. Neural networks. Backpropagation. Over the past year or two, I've heard these buzz words being tossed around a lot, and it's something that has definitely seized my curiosity recently. Deep learning is an area of active research these days, and if you've kept up with the field of computer science, I'm sure you've come across at least some of these terms at least once.

Deep learning can be an indimidating concept, but it's becoming increasingly important these days. Google's already making huge strides in the space with the Google Brain project and its recent acquisition of the London-based deep learning startup DeepMind. Moreover, deep learning methods are beating out traditional machine learning approaches on virtually every single metric.

So what exactly is deep learning? How does it work? And most importantly, why should you even care?

Note to the Reader

If you're new to computer science, and you've follow...