Demystifying Machine Learning and AI in Market Insights

If you are like me, you’re probably reading this article because of the buzzwords in the title. Even though everyone seems to be talking about predictive analytics, machine learning (ML) and AI, definitions for these emerging fields can be hard to come by and, more importantly, few people have a clear vision for how they can benefit their businesses.

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The Most Widely Read GreenBook Blog Posts of 2019

It has become the custom of the GreenBook Blog to publish an article presenting the most widely read articles of the past year.  It is appropriate that we do so again this year, but we decided to make a few changes:
Since we publish over 200 posts a year, instead of presenting a Top 10, we decided to expand the list up to the Top 20.  This way, we could look at roughly the top 10%.

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How Machine Learning And Contract Management Go Together

Last year, Harvard Business Review published a great article on the ways that AI are changing contract management. Author Beverly Rich has said that AI and machine learning will be integral to contracts in the 21st Century.
Rich said that there are some challenges to utilizing AI for contracts. The biggest issue is that the majority of companies don’t retain data on their contracts.

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Big Data Sets Impressive New Standards On Integrated Business Systems

In 2013, Wired published a very interesting article about the role of big data in the field of integrated business systems. Author James Kobielus, the lead AI and data analyst for Wikibon and former IBM expert, said that there are a number of ways that integrated business systems are tapping the potential of AI and big data.

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Will Machine Learning Save The Struggling Airline Industry?

In June, Aviation Today published a great article on the state of machine learning and AI in the airline industry. The article showed that machine learning and AI are helping the industry become more lucrative in the 21st Century.
The airline industry has started relying more on machine learning technology as new challenges threaten to cripple its business.

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Bridging the Gap Between Customer Expectations and Reality in Telco, with Conversational AI

By Henry Iversen, This article is co-authored by Sverre P. Jonassen
Meeting the expectations of consumers in today’s on-demand world is by no means an easy task. They often have sky-high expectations and expect the brands they interact with to be ready to assist their every need 24/7 with instant, helpful and personalized service.

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How One Instagram Influencer Built Her Brand and Attracted 40K Followers

This article was written in the first person by Rafaella Aguiar, Director of Marketing at Kicksta, following an interview with Erin Marie.
Building a big following on Instagram, and doing it fast, takes hard work and dedication — but it’s also one hundred percent possible, and I have the proof.
My name is Erin Marie.

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Orbital resonance in Neptune’s moons

Phys.com published an article a couple days ago NASA finds Neptune moons locked in ‘dance of avoidance’. The article is based on the scholarly paper Orbits and resonances of the regular moons of Neptune.
The two moons closest to Neptune, named Naiad and Thalassa, orbit at nearly the same distance, 48,224 km for Naiad and 50,074 km for Thalassa.

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Lessons from Thinking, Fast & Slow – System 1 and System 2

Editor’s Note:  This article was originally published back in 2012, and due to the popularity of the article, we are bringing it back for your reading pleasure.  You can still access the original article, here.
The Nobel Prize winner and the intellectual godfather of behavioral economics, Daniel Kahneman, has summarized a lifetime of research in his recent book Thinking, Fast & Slow.

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Recent Advances in Deep Learning for Natural Language Processing

This article was original published at The New Stack under the title “How Deep Learning Supercharges Natural Language Processing“.
Voice search, intelligent assistants, and chatbots are becoming common features of modern technology. Users and customers are demanding a better, more human experience when interacting with computers.

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The Netflix Data War

A recent article in the Wall Street Journal, “At Netflix, Who Wins When It’s Hollywood vs. the Algorithm?” by Shalini Ramachandran and Joe Flint details some of the internal debates within Netflix between the Los Angeles-based content team, which is in charge of developing and marketing new content for the streaming service, and the data team.

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Deep Learning Sentiment Analysis for Movie Reviews using Neo4j

While the title of this article references Deep Learning, it’s important to note that the process described below is more of a deep learning metaphor into a graph-based machine learning algorithm. No neural networks are used. Sentiment analysis uses natural language processing to extract features of a text that relate to subjective information found in source materials.

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Discussion of “Fast Approximate Inference for Arbitrarily Large Semiparametric Regression Models via Message Passing”

This article is written with much help by David Blei. It is extracted from a discussion paper on “Fast Approximate Inference for Arbitrarily Large Semiparametric Regression Models via Message Passing”. [link]
We commend Wand (2016) for an excellent description of
message passing (mp) and for developing it to infer large semiparametric
regression models.

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