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Featured Blog Posts – December 2019 Archive (68)

AI Ethics Challenge: Understanding Passive versus Proactive Ethics

Several of my friends have challenged me to get involved in the AI ethics discussion. I certainly do not have any special ethics training. But then again, maybe I do. I’ve been going to church most Sundays (and not just on Christmas Eve) since I was a kid and have been taught a multitude of “ethics” lessons from the Bible. So, respectively, let me take my best shot at sharing my thoughts about the critical importance of the AI Ethics topic.

What is AI…

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Added by Bill Schmarzo on December 31, 2019 at 12:30pm — No Comments

Can Reinforcement Learning Break Through in 2020

Summary:  Reinforcement Learning (RL) is going to be critical to achieving our AI/ML technology goals but it has several barriers to overcome.  While reliability and a reduction in training data may be achievable within a year, the nature of RL as a ‘black box’ solution will bring scrutiny for its lack of transparency.

 …

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Added by William Vorhies on December 30, 2019 at 11:18am — No Comments

It's time for Time-series Databases

The history of Database management systems could be interpreted as a Darwinian evolution process.

The dominance of relational databases gives way to the data warehouses one, which better adapt to the earliest business intelligence requirements; then, alongside the rise of the most popular big data platforms such as Hadoop or spark, comes the era of the NoSQL…

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Added by Valeria on December 30, 2019 at 1:00am — No Comments

Data science cookbook style code reference in Python for beginners

Here is another resource I use for teaching my students at AI for Edge computing course. I like this resource because I like the cookbook style of learning to code. The resource is based on the book Machine…

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Added by ajit jaokar on December 29, 2019 at 11:30pm — No Comments

Weekly Digest, December 30

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.  …

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Added by Vincent Granville on December 29, 2019 at 4:30pm — No Comments

I (kind of) Liked New Math

“When I think back on all the crap I’ve learned in high school, It’s a wonder I can think at all” - Simon and Garfunkel, Kodachrome

Growing up in the ’60s in California, we were subjected to a lot of educational experiments. We had beanbag chairs in class. We squinted into uncomfortable metal and…

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Added by Russell W Anderson on December 28, 2019 at 2:30am — No Comments

Not tools, focusing on problems: a project cycle in data science

As a data scientist in an organization you frequently find yourself in a couple of situations:

  • you have a business…
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Added by Mab Alam on December 27, 2019 at 8:00pm — No Comments

Wanna Build an AI-powered Organization? Start by Getting EVERYONE to “Think Like A Data Scientist”

In a recent blog I stated that “Crossing the AI Chasm" is primarily an organizational and cultural challenge, not a technology challenge. That “Crossing the AI Chasm” not only requires organizational buy-in, but more importantly, necessitates creating a culture of adoption and continuous learning fueled at the front-lines of customer and/or operational engagement (see Figure 1).…

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Added by Bill Schmarzo on December 27, 2019 at 12:00pm — 2 Comments

Business Intelligence Analytics in One Picture

Business intelligence is an umbrella term covering a variety of ways to collect, store and analyze business operations and activities data. This one picture shows you the different processes and methods that make up the business intelligence sphere.

References…

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Added by Stephanie Glen on December 27, 2019 at 9:58am — No Comments

Tech Talk: Sebastian Raschka’s take on TensorFlow 2.0 and the new edition of his widely acclaimed Python Machine Learning book

Through exposure to the news and social media, you are probably familiar with the fact that machine learning has become one of the most exciting technologies of our time. While it may seem that machine learning has become the buzzword of our age, it is certainly not just hype. This exciting field opens up the way to new possibilities and has become indispensable to our daily lives.

Being exposed to practical code examples and working through example applications

of machine…

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Added by Packt Publishing on December 27, 2019 at 1:38am — No Comments

Machine Learning Technical Landscape

The picture below is from the article Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a survey, posted here.

Authors: Giang Nguyen, Stefan Dlugolinsky, Martin Bobák, Viet…

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Added by Capri Granville on December 26, 2019 at 12:00pm — No Comments

Event Conceptualization & Distribution Modelling

In a recent blog, I described the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders as an ontological reference.  I explained how this type of resource can be used for the codification of distributable events in order to build up a database.  In an organization, although the context surrounding the idea of a “disorder” is different;…

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Added by Don Philip Faithful on December 26, 2019 at 7:07am — No Comments

NeurIPS 2019 – analysis of papers by themes

You can always learn a lot from the papers presented at NeurIPS

There is some good analysis already on the web.

From Chip Huygen – neurips 2019 analysis and from David…

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Added by ajit jaokar on December 25, 2019 at 7:54am — No Comments

Predictive Analytics vs Prescriptive Analytics in one picture

Predictive analytics, prescriptive analytics and the fairly recent offshoot-- discovery analytics-- can all support business decision making. Although the three tools are very similar in that they build off the same analytic foundation, the types of decisions they support are quite different. This one picture explains the differences between the three methods.…

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Added by Stephanie Glen on December 24, 2019 at 11:35am — 1 Comment

Ontologies and Semantic Annotation. Part 1: What Is an Ontology

Ontologies and Semantic Annotation. Part 1: What Is an Ontology





In the abundance of…

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Added by Max Ved on December 23, 2019 at 2:31pm — No Comments

A Majority of Data Scientists Lack Competency in Advanced Machine Learning Areas and Techniques

This article was written by Bob Hayes.

Data science requires the effective application of skills in a variety of machine learning areas and techniques. A recent survey by Kaggle, however, revealed that a limited number of data professionals possess competency in advanced machine learning skills. About half of data professionals said they were competent in…

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Added by Andrea Manero-Bastin on December 23, 2019 at 1:00pm — 1 Comment

Reimagining Reinforcement Learning – Upside Down

Summary:  For all the hype around winning game play and self-driving cars, traditional Reinforcement Learning (RL) has yet to deliver as a reliable tool for ML applications.  Here we explore the main drawbacks as well as an innovative approach to RL that dramatically reduces the training compute requirement and time to train.

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Added by William Vorhies on December 23, 2019 at 7:30am — No Comments

The Rise of Biometric Authentication - The Rewards and Risks

Introduction

The utilization of biometrics as a tool for securing and verifying identity has been standard practice among government and law enforcement agencies for quite some time now. Some of the common uses of biometrics include the collection and storage of fingerprints to track government- and state-issued permits and licenses (in the cases of healthcare professionals, passports, drivers’ licenses, etc.), the prevention of…

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Added by Ram Sivasankaran on December 22, 2019 at 5:30pm — No Comments

Weekly Digest, December 23

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.  …

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Added by Vincent Granville on December 22, 2019 at 4:00pm — No Comments

AI and the future of work: Will Artificial Intelligence make us all into Polymaths in the future?

 

AI and the future of work is a major topic of discussion

 

Most views on this subject are negative

 

More broadly, the negative impact of technology has been highlighted by Nicholas Carr (the shallows) ,…

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Added by ajit jaokar on December 22, 2019 at 1:30pm — No Comments

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