## women’s style recommendation with artificial intelligence (part #2)

In “women’s style recommendation with artificial intelligence (part #1)”, I introduced my work toward developing artificial intelligence (AI) for fashion and style recommendation. Essentially, its an expert system built on a Bayesian belief network. Now I discuss model validation and next steps in the design iteration process. I first wanted to see if the trained […]

## women’s style recommendation with artificial intelligence (part #1)

Introduction We know several basic style “rules” (ha!) based on body shape: Skirts: “Apple” Body Shape: IF body shape is apple AND skirt has front zipper THEN don’t wear IF body shape is apple AND skirt has side zipper THEN wear IF body shape is apple AND skirt has no zipper THEN wear “Rectangular” Body […]

## Bayesian method for filtering out mRNA turnover rate bias from siRNA knockdown measurements

Abstract siRNA performance prediction calculations for a given siRNA may be divided into two broad categories: functions of the siRNA’s sequence, hereafter referred to as “intrinsic” properties of the siRNA, and functions of the target mRNA, hereafter referred to as “extrinsic” properties of the siRNA. When training a statistical or machine learning model to select […]

## Bayesian network modeling stock price change

Update 29 April 2018 I suspect this result is erroneous in that the graph often shows two arrows between any two given nodes, one inward and one outward. I’ll investigate this further and get back to you… – Emily Introduction Taking a cue from the systems biology folks, I decided to model stock price change […]

## 21504 to 1 odds the sun will rise tomorrow: an illustration of Bayesian reasoning

The following preposterous case illustrates the Bayesian worldview: Prior estimate If you ask a mathematically-gifted newborn for the probability that the sun will rise tomorrow, they might reply: “The probability that the sun will rise tomorrow follows a beta distribution with parameters a = b = 2.” Since the mean of the above distribution is […]

## data scientist goes coolhunting…

Intuitive coolhunting scales poorly. Here’s some math to help fix that problem: Axioms of cool Five axioms enable us to mathematically model cool: No one is intrinsically cool, individuals simply channel it. Ability to temporarily hold coolness varies by individual. Coolness naturally flows into some individuals more readily than others. Rate of coolness flow into […]