<commit_before>---
title: "Bayes is BAE"
layout: post
published: true
date: 2017-06-12
permalink: /2017/06/12/bayes-is-bae/
categories:
    - ruby
---

For my 2017 RailsConf I spoke about Probability and Bayes Rule. Here's the abstract:

> Before programming, before formal probability there was Bayes. He introduced the notion that multiple uncertain estimates which are related could be combined to form a more certain estimate. It turns out that this extremely simple idea has a profound impact on how we write programs and how we can think about life. The applications range from machine learning and robotics to determining cancer treatments. In this talk we'll take an in depth look at Bayses rule and how it can be applied to solve problems in programming and beyond.

If you're interested in going down the deep end in probability and Kalman Filter's I hope you enjoy my talk:

## Video

<iframe width="560" height="315" src="https://www.youtube.com/embed/bQSzZrDDV80" frameborder="0" allowfullscreen></iframe>

## Slides

<script async class="speakerdeck-embed" data-id="26015c2545544d9d9d689f17a903bc43" data-ratio="1.77777777777778" src="//speakerdeck.com/assets/embed.js"></script>

> There's a lot of transitions and video which don't translate to export to PDF, also I have a technique of putting multiple slides of the same content in a row so that I can get different speaker notes without you knowing that i'm flipping slides. In sort the slides were meant to be presented, not viewed statically on the web, yet here we are.

## Transcript

What if you could predict the future? What if we all could? I'm here today to tell you ... That you can. We all can. We have the power to predict the future. The bad news, is that we're not very good at it. The good news? Is that even a bad prediction can tell us something about the future. Today, we will predict. Today, we will learn. Today, we will discover why Bayes is bae.

Introducing our protagonist, this is <NAME>.

Thomas was born in 1701, maybe, we don't exactly know.

He was born to a town called Hertfordshire.

 No? No, close?

 Possibly, we can't know for certain.

 We don't actually even know what Bayes looked like.

 What we do know is that Bayes was a Presbyterian minister and a statistician. We also know that his most famous work was published, a paper, that gave us Bayes Rule, was not published until after his death. Before this he published two other papers. "The Diving Benevolence, or an Attempt to Prove That the Principal End of the Divine Providence and Government is the Happiness of his Creatures". Yes, that is one title. As well as, "An Introduction of the Doctrine of Fluxions, and a Defense of the Mathematicians Against the Objections of the Author of The Analyst". I like my titles a little bit shorter but everybody has different preferences.

Why do we care about this? Well, Bayes contributed significantly to probability with the formulation of Bayes Rule. Again, even though it wasn't published until after his death, let's travel back and put our minds in a commoner of the era. The year is 1720. Sweden and Prussia just signed the treaty of Stockholm. <NAME>, the mother of the person who wrote the requiem that we just enjoyed, <NAME>, so not Mozart, but his mother was born in 1720. Statistics is all of the rage, as well as probabilities. At the time, we can know things like, "Given we know the umber of winning tickets at a raffle, what is the probability of any one given ticket will be a winner?"
<commit_msg>Better blurb<commit_after>---
title: "Bayes is BAE"
layout: post
published: true
date: 2017-06-12
permalink: /2017/06/12/bayes-is-bae/
categories:
    - ruby
---

Before programming, before formal probability there was Bayes. He introduced the notion that multiple uncertain estimates which are related could be combined to form a more certain estimate. It turns out that this extremely simple idea has a profound impact on how we write programs and how we can think about life. The applications range from machine learning and robotics to determining cancer treatments. In this talk we'll take an in depth look at Bayses rule and how it can be applied to solve problems in programming and beyond.

This is the talk that I gave at RailsConf 2017. It's about math, probability and programming.

If you're interested in going down the deep end in probability and Kalman Filter's I hope you enjoy my talk.

## Video

<iframe width="560" height="315" src="https://www.youtube.com/embed/bQSzZrDDV80" frameborder="0" allowfullscreen></iframe>

## Slides

<script async class="speakerdeck-embed" data-id="26015c2545544d9d9d689f17a903bc43" data-ratio="1.77777777777778" src="//speakerdeck.com/assets/embed.js"></script>

> There's a lot of transitions and video which don't translate to export to PDF, also I have a technique of putting multiple slides of the same content in a row so that I can get different speaker notes without you knowing that i'm flipping slides. In sort the slides were meant to be presented, not viewed statically on the web, yet here we are.

## Transcript

What if you could predict the future? What if we all could? I'm here today to tell you ... That you can. We all can. We have the power to predict the future. The bad news, is that we're not very good at it. The good news? Is that even a bad prediction can tell us something about the future. Today, we will predict. Today, we will learn. Today, we will discover why Bayes is bae.

Introducing our protagonist, this is <NAME>.

Thomas was born in 1701, maybe, we don't exactly know.

He was born to a town called Hertfordshire.

 No? No, close?

 Possibly, we can't know for certain.

 We don't actually even know what Bayes looked like.

 What we do know is that Bayes was a Presbyterian minister and a statistician. We also know that his most famous work was published, a paper, that gave us Bayes Rule, was not published until after his death. Before this he published two other papers. "The Diving Benevolence, or an Attempt to Prove That the Principal End of the Divine Providence and Government is the Happiness of his Creatures". Yes, that is one title. As well as, "An Introduction of the Doctrine of Fluxions, and a Defense of the Mathematicians Against the Objections of the Author of The Analyst". I like my titles a little bit shorter but everybody has different preferences.

Why do we care about this? Well, Bayes contributed significantly to probability with the formulation of Bayes Rule. Again, even though it wasn't published until after his death, let's travel back and put our minds in a commoner of the era. The year is 1720. Sweden and Prussia just signed the treaty of Stockholm. <NAME>, the mother of the person who wrote the requiem that we just enjoyed, <NAME>, so not Mozart, but his mother was born in 1720. Statistics is all of the rage, as well as probabilities. At the time, we can know things like, "Given we know the umber of winning tickets at a raffle, what is the probability of any one given ticket will be a winner?"

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