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Weekly Digest, March 9

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 March 7, 2020 at 10:00am — No Comments

The case for open data for AI in the fight against COVID-19

I saw a post recently which claimed that AI can help doctors diagnose coronavirus

On the face of it - this sounds like a positive development but I wonder if it is?

As I understand it,  a single Chinese…

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Added by ajit jaokar on March 6, 2020 at 12:09pm — 1 Comment

The True Value of Legacy Systems Modernization for Businesses

To stay relevant businesses should always take the path of innovation: what was effective a few years ago today just might not be that effective. In this article, I would like to talk about Legacy Systems Modernization and why should you do anything you can to keep your processes up-to-date, with the…

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Added by Roman Chuprina on March 6, 2020 at 3:30am — No Comments

Compressing information through the information bottleneck during deep learning

This article was written by Ray.

Read an article in Quanta Magazine (New theory cracks open the black box of deep learning) about a talk (see 18: Information Theory of Deep Learning, YouTube video) done a month or so ago given by Professor Naftali (Tali) Tishby on his theory that all deep learning convolutional neural networks (CNN) exhibit an “information bottleneck”…

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Added by Andrea Manero-Bastin on March 6, 2020 at 3:00am — No Comments

Who All Can Benefit From the Implementation of the Energy Monitoring Solution?

No doubt, the technology of Internet of Things is swelling at an extraordinary rate. One sector that has benefited significantly from this technological marvel is the powerhouse sector of energy.

In 2015, the global energy market reached a valuation of USD 6.8 billion and is now expected to reach $26.5 billion by the end of…

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Added by Sanjeev Verma on March 5, 2020 at 11:30pm — No Comments

Thursday News, March 5

Here is our selection of featured articles and technical resources posted since Monday.

Announcements

Technical Resources

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Added by Vincent Granville on March 5, 2020 at 11:30am — No Comments

How Data Cleansing and Enrichment Increases Profitability

In today's hyper-competitive business world, B2B & B2C businesses rely on data to achieve an edge in their markets. However, many companies do not realize that customer data decays rapidly and create challenges in achieving business goals. In the postmodern era, customers simply change base too often, and to maintain a complete and accurate record of their whereabouts is a challenging task. Dirty data not only damages your credibility but also costs you money…

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Added by Chirag Shivalker on March 4, 2020 at 9:24pm — No Comments

9 Cities To Get Hired as a Data Scientist for 2020

We talk a lot about how to get hired as data scientists, but it’s time for our annual roundup of where to get hired as a data scientist for 2020. Without further ado, here are the top picks for best data science cities, and they couldn’t be a more diverse bunch.

Some offer the most exciting tech advances. Others have an excellent cost of living. Some have thriving and supportive communities. All of them are fantastic places to get your first (or next) data science…

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Added by ODSC on March 4, 2020 at 9:30am — No Comments

The 2020 Data Science Dictionary—Key Terms You Need to Know

As I discussed early last year, the data science field is a virtual hot-bed of terminology, a confluence of terms from computer science, statistics, mathematics, and software engineering. In addition, the language of data science evolves very quickly. As a journalist and also a data scientist, I probably see the newest terms before many others in the…

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Added by ODSC on March 4, 2020 at 9:00am — No Comments

Schmarzo’s Economic Digital Asset Valuation Theorem Formulas

I’ve had several folks tell me that if I can’t convert the “effects” in the Schmarzo "Economic Digital Asset Valuation Theorem” into mathematical equations, that my quest for a Nobel Prize in Economics would be greatly hindered.  So, I enlisted the help of my senior data science team of Wei Lin, Mauro Damo and Yong Zhang to help me address this problem (they were only diverted from small projects related to preserving our rainforests, improving healthcare and reducing carbon…

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Added by Bill Schmarzo on March 4, 2020 at 5:00am — 1 Comment

Data Visualization 101: 4 Tips To Convert Data To Information Quickly

Data science is all about extracting the information from the data gathered. As data has become one of the essential entities in today's world, it drives substantial business profits. It also inspires many to launch their startup based on the assessments they perform of the…

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Added by Shady Johnson on March 4, 2020 at 2:30am — No Comments

How to Pick a Winning March Madness Bracket

by Robert Robison, Data Analyst, Elder Research

In 2019, over 40 million Americans wagered money on March Madness brackets, according to the American Gaming Association. Most of this money was bet in “bracket…

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Added by Paul Derstine on March 3, 2020 at 7:30am — No Comments

What are Data Lakes ?

Some of you are highly organized, disciplined, and keep all your belongings arranged in an ordered manner. You can easily remember the location of all these items and will be able to fetch them in a short time. But there are people who are highly unorganized and keeps all their belongings in a random manner and will have no clue on where to look for an item when they really need it. This results in a search operation on all storage spaces in the house when they want to fetch an item. There is… Continue

Added by Janardhanan PS on March 2, 2020 at 9:37pm — No Comments

Making Sense of the Hype Cycle for Artificial Intelligence

Summary:  If you’re planning your AI/ML business strategy watch out for the confusion in categories and overly risky ratings given by some research and review sources.  Read the research, then consult with your own data scientists for a better evaluation of risk. It’s likely not as bad as you think. 

 …

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Added by William Vorhies on March 2, 2020 at 12:42pm — No Comments

Introduction to Numpy - A Math Library for Python

This article was written by Vasudev.

Lets get started quickly. Numpy is a math library for python. It enables us to do computation efficiently and effectively. It is better than regular python because of it’s amazing capabilities.

In this article I’m just going to introduce you to the basics of what is mostly required for machine learning and…

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Added by Andrea Manero-Bastin on March 1, 2020 at 12:00pm — 1 Comment

Weekly Digest, March 2

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 March 1, 2020 at 11:00am — No Comments

State-of-the-Art Statistical Science to Tackle Famous Number Theory Conjectures

The methodology described here has broad applications, leading to new statistical tests, new type of ANOVA (analysis of variance), improved design of experiments, interesting fractional factorial designs, a better understanding of irrational numbers leading to cryptography, gaming and Fintech applications, and high quality random number generators (and when you really need them). It also features exact arithmetic / high performance computing and distributed algorithms to compute millions of…

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Added by Vincent Granville on February 29, 2020 at 9:00pm — No Comments

Different Probability Distributions in One Picture

Data science uses many different probability distributions, but some are used more than others. This one picture shows an overview of five probability distributions data scientists will  find the most useful. See below the image for more information about the distributions.

Further Information:…

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Added by Stephanie Glen on February 29, 2020 at 3:00pm — No Comments

Be Forewarned CEO’s; Build Out Your Data Science Capabilities or Perish

We all know how horror movies work: there is someone evil in the neighborhood (like Michael Myers in “Halloween” or Freddy Krueger in “Nightmare on Elm Street” or Tom Cruise in “War of the Worlds”) and the soon-to-be-victim, we’ll say in this case, an unassuming CEO, wanders into a dark space (basement, closet, wood shed, attic) where the evil doer is waiting for them with a new agenda for the digital enterprise they can’t assimilate and they perish.

Slash! Cut! Gouge! Scream!…

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Added by Bill Schmarzo on February 27, 2020 at 10:30pm — No Comments

How you can explain Machine Learning models ?

Machine Learning (ML) models are increasingly being used to augment human decision making process in domains such as finance, telecommunication, healthcare, and others. In most of the cases, users do not understand how these models make predictions. The lack of understanding makes it difficult for policy makers to justify their decisions. Most of the ML models are black boxes that do not explain on its own why it reached a specific recommendation or a decision. This forces the users to say…

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Added by Janardhanan PS on February 27, 2020 at 7:00pm — No Comments

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