Group items tagged

"Caution! Page goes deep into the mathematical theory behind prediction and group behaviour. Unless you are comfortable with 'the math', you will find this tough going."

Prediction Markets is planned to be one of the topics at the 2009 winter workshop

Video talking about how US company 'Best Buy' uses prediction markets

From Jed Christanson's blog - predictin market software review

For a fascinating item relevant to Prediction Markets, listen to thisBBC Radio 4 'More or Less' item on The Recognition Heuristic' (from 9 mins 55 secs to 16 mins 47 secs).

For a fascinating item relevant to Prediction Markets, listen to this 'More or Less' item on The Recognition Heuristic' (from 9 mins 55 secs to 16 mins 47 secs).

McKinsey have developed an approach to retention: to detect previously unobserved behavioural patterns, they combine various data sources with machine-learning algorithms. Workshops and interviews are used to generate ideas and a set of hypotheses. Over time they collected hundreds of data points to test. Then ran different algorithms to get insights at a broad organisational level, to identify specific employee clusters, and to make individual predictions. Finally they held a series of workshops and focus groups to validate the insights from our models and to develop a series of concrete interventions. The insights were surprising and at times counterintuitive. They expected factors such as an individual's performance rating or compensation to be the top predictors of unwanted attrition. But analysis revealed that a lack of mentoring and coaching and of "affiliation" with people who have similar interests were actually top of list. More specifically, "flight risk" across the firm fell by 20 to 40 percent when coaching and mentoring were deemed satisfying.

McKinsey have developed an approach to retention: to detect previously unobserved behavioural patterns, they combine various data sources with machine-learning algorithms. Workshops and interviews are used to generate ideas and a set of hypotheses. Over time they collected hundreds of data points to test. Then ran different algorithms to get insights at a broad organisational level, to identify specific employee clusters, and to make individual predictions. Finally they held a series of workshops and focus groups to validate the insights from our models and to develop a series of concrete interventions. The insights were surprising and at times counterintuitive. They expected factors such as an individual's performance rating or compensation to be the top predictors of unwanted attrition. But analysis revealed that a lack of mentoring and coaching and of "affiliation" with people who have similar interests were actually top of list. More specifically, "flight risk" across the firm fell by 20 to 40 percent when coaching and mentoring were deemed satisfying.

In machine learning, computers apply statistical learning techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions. This animated presentation explains machine learning in simple to follow graphics.

"Some bright bulb at Microsoft Research had the clever idea of turning a machine learning program loose on Twitter yesterday to learn how humans interact with each other. Humans, predictably, interacted terribly."

"A little more than a year ago, Gartner said gamification was being "driven by novelty and hype" and that by 2014, 80 percent of current gamified applications will "fail to meet business objectives primarily because of poor design.""

IBM - Watson Analytics and Prediction Engine

Many companies are seeing that the future of deep learning is here, and that it doesn't require a lot of money or resources to take advantage of this new industrial science. IBM's Watson Analytics offers a freemium service that allows you to upload up to 500MB, and enables you to explore your own real-life applications for deep learning. Inputting Google Adwords or other sales metrics into this tool can help even startup companies find relational and predictive information in their data.

Amazon Web Services announced that it was selling to the public the same kind of software it uses to figure out what products Amazon puts in front of a shopper, when to stage a sale or who to target with an email offer. The techniques, called machine learning, are applicable for technology development, finance, bioscience or pretty much anything else that is getting counted and stored online these days. In other words, almost everything.

"Using prediction market to forecast pharmaceutical development success (courtesy Jenny Ambrozek)"