A Markov Chain is a random process, where we assume the previous state(s) hold sufficient predictive power in predicting the next state. Unlike flipping a coin, these events are dependent. It’s easier to understand through an example.…

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Most people (including myself) are drawn to Julia by its lofty goals. Speed of C, statistical packages of R, and ease of Python?—it sounds two good to be true. However, I haven't seen anyone who has looked into it say the developers behind the language aren't on track to accomplish these goals.…

ContinueAdded by Alex Woods on August 23, 2015 at 4:30pm — No Comments

A Markov Chain is a random process, where we assume the previous state(s) hold sufficient predictive power in predicting the next state. Unlike flipping a coin, these events are dependent. It’s easier to understand through an example.…

Added by Alex Woods on August 4, 2015 at 8:00pm — No Comments

I’m going to keep this tutorial light on math, because the goal is just to give a general understanding.

The idea of Monte Carlo methods is this—*generate some random samples for some random variable of interest, then use these samples to compute values you’re interested in*.

I know, super broad. The truth is Monte Carlo has a ton of different applications. It’s…

ContinueAdded by Alex Woods on July 25, 2015 at 6:00pm — 5 Comments

Linear regression is one of the first things you should try if you’re modeling a linear relationship (actually, non-linear relationships too!). It’s fairly simple, and probably the first thing to learn when tackling machine learning.

At first, linear regression shows up just as a simple equation for a line. In machine learning, the weights are usually represented by a vector θ (in statistics they’re often represented…

ContinueAdded by Alex Woods on July 19, 2015 at 8:31am — 1 Comment

It’s important to know what goes on inside a machine learning algorithm. But it’s hard. There is some pretty intense math happening, much of which is linear algebra. When I took Andrew Ng’s course on machine learning, I found the hardest part was the linear…

ContinueAdded by Alex Woods on July 10, 2015 at 10:30pm — No Comments

Random Forest is a machine learning algorithm used for classification, regression, and feature selection. It's an ensemble technique, meaning it combines the output of one weaker technique in order to get a stronger result.

The weaker technique in this case is a decision tree. Decision trees work by splitting the and re-splitting the data by…

ContinueAdded by Alex Woods on July 4, 2015 at 8:30am — No Comments

When you're cleaning up data, you usually end up using a 5-8 functions a ton of times, and then a few more once or twice. Here are those 5-8 functions I find myself using again and again.

Here is a quick overview:

names() - returns the column names of a dateset…

ContinueAdded by Alex Woods on July 4, 2015 at 8:00am — No Comments

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