Find a wide variety of data including demographic, environment, financial, retail and sports. Use this data in your Microsoft Office software, BI tools and your very own custom applications.

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MIOsoft

MIOsoft geographic coordinates generator

published by: MIOsoft

MIOsoft geographic coordinates generator enables you to generate 100 coordinates per Webservice Call limited by a bounding box or an ISO standard country code. The coordinates are spread within this area based on the population density. This service is meant to generate geographic testdata.

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Azure Machine Learning

Text Analytics

published by: Azure Machine Learning

Text Analytics API is a suite of text analytics services built with Azure Machine Learning. Just bring your unstructured text (English only), and use this API to perform sentiment analysis and key phrase extraction.

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Versium Analytics Inc

Green Score

published by: Versium Analytics Inc

Versium’s Green Score helps businesses identify customers who have a high likelihood of making more environmentally conscious purchase decisions so they can better target marketing campaigns and optimize lead qualification programs. The higher the Green Score, the more likely the customer or prospect will purchase green product or services.

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Versium Analytics Inc

Wealth Score

published by: Versium Analytics Inc

Versium’s Wealth Score can help companies understand the estimated net worth of their customers and prospects so they can better target their marketing campaigns and optimize their lead qualification programs. The higher the Wealth Score, the more likely the customer or prospect has a high net worth.

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Versium Analytics Inc

Giving Score

published by: Versium Analytics Inc

Versium’s Giving Score helps organizations understand which of their current contributors have a higher propensity to make larger donations and become repeat donors, as well as predicting the propensity of a prospect to donate to a charity or other organization. The higher the Giving Score, the more likely the customer or prospect will donate.

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Azure Machine Learning

Frequently Bought Together

published by: Azure Machine Learning

Frequently Bought Together is a market basket analysis API built with Azure Machine Learning. It helps your customers discover items in your catalog that are frequently purchased together. Use your purchase history to add recommendations to your website.

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Azure Machine Learning

Anomaly Detection

published by: Azure Machine Learning

Anomaly Detection API runs different types of detectors on time series data and gives alerts when unusual patterns in the time series are detected.

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Azure Machine Learning

Binary Classifier API built with Azure Machine Learning

published by: Azure Machine Learning

Binary Classifier API is an example built with Microsoft Azure Machine Learning that fits a logistic regression model to user inputted data and outputs the predicted value for each of the observations in the data. Suppose you have a dataset and would like to predict a binary dependent variable based on the independent variables. ‘Logistic Regression’ is a popular statistical technique used for such predictions. Here the dependent variable is binary or dichotomous and 'p' is the probability of presence of the characteristic of interest. A simple scenario could be where the researcher is trying to predict whether the prospective student is likely to accept the admission offer to a university based on information (GPA in high school, family income, resident state, gender). The predicted outcome is the probability of a prospective student accepting their admission offer.

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Azure Machine Learning

Cluster Model API built with Azure Machine Learning

published by: Azure Machine Learning

Cluster Model API is an example built with Microsoft Azure Machine Learning that classifies a set of observations into two or more mutually exclusive unknown groups based on combinations of variables. The purpose of cluster analysis is to discover a system of organizing observations, usually people or their characteristics, into groups, where members of the groups share properties in common. This web service uses the K-Means methodology, a commonly used clustering technique, to cluster arbitrary data into groups. This web service takes the data and the number of clusters k as input, and produces predictions of which of the k groups to which each observations belongs.

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Azure Machine Learning

Multivariate Linear Regression API built with Azure Machine Learning

published by: Azure Machine Learning

Multivariate Linear Regression API is an example built with Microsoft Azure Machine Learning that fits a linear regression model to user inputted data and outputs the predicted value for each of the observations in the data. Suppose you have a dataset and would like to predict a dependent variable y for each individual based on the other independent variables (x1,x2,…,xn). Linear Regression is a popular statistical technique used for such predictions. A simple scenario could be trying to predict the weight of an individual based on their height. A more advanced scenario could be predicting based on additional information for the individual (such as height, gender, and race).

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