TruFactor Intelligence-as-a-Service Now Available on AWS Data Exchange, Powering AI and Machine Learning At-Scale

At re:Invent, TruFactor, debuts 40+ offerings as a Launch Partner for AWS Data Exchange, making consumer intelligence easily accessible to millions of AWS customers
TruFactor, an InMobi Group company, announced at AWS re:Invent 2019 that over 40 TruFactor intelligence offerings tailored to specific use cases and industries are now available on AWS Data Exchange, a new service that makes it easy fo

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With Product Video Marketing, Customers Are Instantly Captivated and Conversions Become Effortless!

The e-commerce industry is a wonderful thing. Business owners can set up shop and start making sales to buyers all over the world in no time. Shoppers enjoy endless options from stores and brands across the globe. But despite the many advantages it offers both buyers and business owners, it can be challenging for online retailers to come up with new and exciting ways to wow their online audience.

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Grids and graticules in the tmap package

This vignette builds on the making maps chapter of the Geocomputation with R book.
Its goal is to demonstrate how to set and modify grids and graticules in the tmap package.
Prerequisites
The examples below assume the following packages are attached:
library(spData) # example datasets
library(tmap) # map creation (>=2.

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How to Do Market Research: A 6-Step Guide

Today’s buyers hold all of the power when making a purchasing decision. You’re also likely aware that they’re doing some of their research online.
But have you really adapted your marketing plan to match the way today’s customers shop and buy?
Consider three recent statistics about consumer behavior:
80% of Instagram users currently follow a business account..

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An Introduction to Forecasting

Forecasting is concerned with making predictions about future observations by relying on past measurements. In this article, I will give an introduction how ARMA, ARIMA (Box-Jenkins), SARIMA, and ARIMAX models can be used for forecasting given time-series data.
Preliminaries Before we can talk about models for time-series data, we have to introduce two concepts.

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Download a Chapter of Data Mining Techniques (3rd Edition) for Free

As seen on KDNuggets, you may now download Chapter 19, Derived Variables: Making the Data Mean More for free, thanks to our friends at JMP. This chapter is one of my personal favorites because it is about the part of data mining I find most enjoyable–thinking of ways to expose more of the information hidden in a data set so predictive algorithms are able to make use of it.

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Label line ends in time series with ggplot2

@drsimonj here with a quick share on making great use of the secondary y axis with ggplot2 – super helpful if you’re plotting groups of time series!
Here’s an example of what I want to show you how to create (pay attention to the numbers of the right):
Setup #
To setup we’ll need the tidyverse package and the Orange data set that comes with R.

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Developing a business strategy by combining machine learning with sensitivity analysis

Machine learning (ML) is routinely used by countless businesses to assist with decision making. In most cases, however, the predictions and business decisions made by ML systems still require the intuition of human users to make judgment calls.
In this post, I show how to combine ML with sensitivity analysis to develop a data-driven business strategy.

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You can replicate almost any plot with R

Although R is great for quickly turning data into plots, it is not widely used for making publication ready figures. But, with enough tinkering you can make almost any plot in R. For examples check out the flowingdata blog or the Fundamentals of Data Visualization book.
Here I show five charts from the lay press that I use as examples in my data science courses.

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