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5 Things You Need to Know from IIeX Behaviour UK 2019

Editor’s Note: Recently, we published an overview of key points from the IIeX Behavior US, in North America. We’ve also just had an IIeX Behaviour in the UK.  Here, Matthew Hellon and Ellie Jacobs summarize the highlights from the UK conference.
IIeX Behaviour UK 2019 was an interesting snapshot of how market researchers are adopting behavioral science.

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Kubernetes: A simple overview

Get a basic understanding of Kubernetes and then go deeper with recommended resources.This overview covers the basics of Kubernetes: what it is and what you need to keep in mind before applying it within your organization.
The information in this piece is curated from material available on the O’Reilly online learning platform and from interviews with Kubernetes experts.

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Interpreting predictive models with Skater: Unboxing model opacity

A deep dive into model interpretation as a theoretical concept and a high-level overview of Skater.Over the years, machine learning (ML) has come a long way, from its existence as experimental research in a purely academic setting to wide industry adoption as a means for automating solutions to real-world problems.

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How new tools in data and AI are being used in health care and medicine

An overview of applications of new tools for overcoming silos, and for creating and sharing high-quality data.Artificial intelligence (AI) will have a huge impact on health care. It is currently moving out of the laboratory and into real-world applications for health care and medicine.

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Recurrent Neural Network Tutorial for Artists

This post is not meant to be a comprehensive overview of recurrent neural networks. It is intended for readers without any machine learning background. The goal is to show artists and designers how to use a pre-trained neural network to produce interactive digital works using simple Javascript and p5.js library.

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Document worth reading: “Deep Reinforcement Learning”

We discuss deep reinforcement learning in an overview style. We draw a big picture, filled with details. We discuss six core elements, six important mechanisms, and twelve applications, focusing on contemporary work, and in historical contexts. We start with background of artificial intelligence, machine learning, deep learning, and reinforcement learning (RL), with resources.

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Peering into the Black Box : Visualizing LambdaMART

In the last post, I gave a broad overview of the Learning to Rank domain of machine learning that has applications in web search, machine translation, and question-answering systems. In this post, we’ll look at a state of the art model used in Learning to Rank called LambdaMART. We’ll take a look at some math underlying LambdaMART, then focus on developing ways to visualize the model.

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