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predictive model
How Businesses Can Use AI to Automate Predictive Modeling
In business, the value of being able to accurately predict outcomes – asset failures, market fluctuations, or customer churn, for example – can scarcely be understated. The growth of data analytics in business in recent years is largely attributable to growing demand for predictive modeling. Today, artificial intelligence is making... Read more
This is the second post in a two-part series that discusses healthcare predictive and propensity modeling and selecting the optimal analytics partner to support your growth and engagement efforts. The first post in this series shares five best practices in healthcare propensity modeling. In our last post, we talked about big data,... Read more
Are Your Predictive Models like Broken Clocks?
A wise philosopher (or comedian) once said, “Even a broken clock is right twice a day.” That same statement might also apply to some predictive models. Since prediction is about the future (usually), then random chance (like broken clockwork) may allow our model to be right occasionally (just by accident). The important... Read more
Actuaries are bringing Netflix-like predictive modeling to health care
I’m an actuary. That means I use numbers to try to understand human behavior, manage risk, and evaluate the likelihood that a particular thing will happen in the future. Most people associate my work with green eyeshades and the morbid business of predicting how long someone is likely to live.... Read more
Predictive Modeling Workshop – Max Kuhn ODSC Boston 2015
Predictive Modeling Workshop from odsc The workshop is an overview of creating predictive models using R. An example data set will be used to demonstrate a typical workflow: data splitting, pre-processing, model tuning and evaluation. Several R packages will be shown along with the caret package which provides a unified... Read more
Getting Started with Predictive Maintenance Models
This was originally posted on the Silicon Valley Data Science blog. In a previous post, we introduced an example of an IoT predictive maintenance problem. We framed the problem as one of estimating the remaining useful life (RUL) of in-service equipment, given some past operational history and historical run-to-failure data. Reading that post... Read more
Ensemble Models Demystified
Ensemble models give us excellent performance and work in a wide variety of problems. They’re easier to train than other types of techniques, requiring less data with better results. In machine learning, ensemble models are the norm. Even if you aren’t using them, your competitors are. Kevin Lemagnen is going... Read more
Crisis Intervention and Saving Lives with NLP & Predictive Analytics
Editor’s note: Tom is a speaker for ODSC East 2019 this April 30-May 3! Be sure to attend his talk, “Crisis Intervention and Saving Lives with Natural Language Processing & Predictive Analytics.” The field of predictive modeling is still young, but one of the most effective trailblazers is Crisis Text... Read more
Reading Tea Leaves: Principles of Predictive Analytics and the Path to Time-Series Predictions
Scott is presenting at ODSC East 2019 this May in Boston! Check out his workshop “Real-ish Time Predictive Analytics with Spark Structured Streaming.” With the advent of so many wonderful open-source tools and frameworks for machine learning & deep learning,  it can sometimes be difficult to understand just what defines... Read more