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Featured Blog Posts – May 2020 Archive (53)

Weekly Digest, June 1

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…

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Added by Vincent Granville on May 31, 2020 at 11:00am — No Comments

Misleading Graphs Part 1: Avoid These Common Mistakes

Misleading graphs are abound on the internet. Sometimes they are deliberately misleading, other times the people creating the graphs don't fully understand the data they are presenting. "Classic" cases of misleading graphs include leaving out data, not labeling data properly, or skipping numbers on the vertical axis.

I came across the following misleading graphic in a…

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Added by Stephanie Glen on May 31, 2020 at 8:00am — 1 Comment

The Problem with Data Science Interviews

The messiest job of the 21st century 

The interview process is likely the most daunting task a data scientist will face in their career. The pressure and competition to…

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Added by VC Martins on May 30, 2020 at 11:00am — No Comments

A Fundamental Theorem for Epidemiology

The work of an Italian mathematician in the 1930s may hold the key to epidemic modeling.

That's because models that try to replicate reality in all its detail have proven hard to steer during this crisis, leading to poor predictions despite noble and urgent efforts to recalibrate them. On the other hand overly stylized compartmental models have run headlong into paradoxes such as Sweden's herd immunity.…

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Added by Peter Cotton on May 28, 2020 at 5:30am — No Comments

New Probabilistic Approach to Factoring Big Numbers

Product of two large primes are at the core of many encryption algorithms, as factoring the product is very hard for numbers with a few hundred digits. The two prime factors are associated with the encryption keys (public and private keys). Here we describe a new approach to factoring a big number that is the product of two primes of roughly the same size. It is designed especially to handle this problem and identify flaws in encryption algorithms.  

While at first glance it appears…

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Added by Vincent Granville on May 27, 2020 at 8:00am — No Comments

A free self-paced learning path for #machinelearning and #deeplearning

In various formats, one of the most frequent questions I am asked is the equivalent of:

“Can you recommend a free self-paced learning path for #machinelearning and #deeplearning?”

In this post, I attempt an answer

This is based on my work / teaching students primarily at Oxford University, but I…

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Added by ajit jaokar on May 26, 2020 at 1:59pm — No Comments

Analytics Translators: Fact or Fiction?

It's been two years since Mckinsey invented the term analytics translator, called it the ‘new must-have role’ and predicted we’d need around 5 million of them.

FIVE MILLION

That’s a bit more than the entire population of Los Angeles, but just slightly less than all of Norway.

For the past ten years, we’ve struggled with the ambiguous title ‘data scientist’, then ‘citizen data scientist’. Now it’s ‘analytics translator’.

Although I've seen many 'data…

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Added by David Stephenson on May 26, 2020 at 8:00am — No Comments

Simulated Statistics is the New Black

Over the years I’ve often been asked by beginners where they should start in statistics, what they should do first, and which parts of statistics they should prioritise to get them to where they want to be (which is usually a higher…

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Added by Lee Baker on May 26, 2020 at 6:30am — No Comments

Data Stewardship in an AI-Driven Ecosystem: Introducing WhiteNoise

 WhiteNoise is the newly available Differential Privacy System by OpenDP.  The intent of Differential Privacy is to preserve the security of personally identifiable information & prevent against database reconstruction attacks.  The methods provided by the WhiteNoise system are part of a toolkit that enable researchers to readily enhance their existing processes with differential privacy techniques. 

The Differential Privacy System

The Differential Privacy…

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Added by alicia moniz on May 25, 2020 at 5:30pm — No Comments

Differential ML on TensorFlow and Colab

Brian Huge and I just posted a working paper following six months of…

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Added by Antoine Savine on May 25, 2020 at 11:30am — No Comments

Do You Need an AI Product Manager

Summary:  What is an AI Product Manager and how do you know when you need one.

 

The role of Product Manager (PM) can mean many things dependent on the specifics of the company, its markets, its channels, and the variety of its products.  It’s almost impossible to put a single label on the responsibilities of a…

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Added by William Vorhies on May 25, 2020 at 10:23am — 2 Comments

Digital Strategy Series Part I: Creating a Data Strategy that Delivers Value

Oh, the strategy pundits hate me! It’s not because I’m tall, good looking and from Iowa (well, 2 out of 3 ain’t bad), it’s because I think Strategy as a “Discipline” is way overblown.  I won’t go as far as the Harvard Business Review to state that “Strategy is Dead”, but the importance of carefully defining a strategy (typically done in the ivory towers of the puzzle palace) and then commanding all the little soldiers to follow the strategy script are over!

Former World…

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Added by Bill Schmarzo on May 24, 2020 at 3:00pm — No Comments

Weekly Digest, May 25

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.  

Featured Resources and…

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Added by Vincent Granville on May 24, 2020 at 12:30pm — No Comments

Statistics Used in Data Science (A Dictionary in One Picture)

Naming conventions are often quite different in statistics and data science, which causes quite a bit of confusion. Part of the problem with naming conventions is  that "...data science is the child of statistics and computer science” (Blei & Symth, 2017) . In essence, data science then is the child of two parents who speak different languages. In one sense, this makes the job of the data scientist not only to apply the knowledge from both…

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Added by Stephanie Glen on May 24, 2020 at 12:08pm — No Comments

AI superpowers – for people and jobs

 

Introduction

In this post, I argue that

  • The idea of AI Superpowers could also apply to people and not only nations.
  • Post COVID the biggest change will be the loss of the factory assembly line (the 1920s Henry Ford model and Frederic Taylor's division of labor ideas)
  • A new class of ‘worker’ - if we may call them…
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Added by ajit jaokar on May 23, 2020 at 2:00pm — No Comments

The Most Important Fundamentals of PyTorch you Should Know

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Added by James Montantes on May 22, 2020 at 11:00am — No Comments

What are “Recurrent Neural Networks”, and how it is different than “Convolutional Neural Networks”

CNN and RNN are amongst most important algorithm of Neural Network family, also they differ in their network process and solving problems.

So talking about their differences:

CNN are used to solve classification and regression problems and RNN are used to solve sequence information.

CNN are used for 2D image…

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Added by Sameer Nigam on May 21, 2020 at 12:00pm — No Comments

Entropy of rolling dices

The Entropy is one of the most important concepts in many fields like physics, mathematics, information theory, etc.

Entropy is related to the number of states that one stochastic system can take and how this system will evolve with time, in such a way that the uncertainty will be maximized.

This will happened y two ways, first, every system will choose the configuration with a higher degree of entropy among all that are available and second, if we let the system evolve, after…

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Added by Pablo Gutierrez on May 21, 2020 at 6:53am — No Comments

Quantum Bayesian Network view of hybrid quantum-classical computation

Introduction



Hybrid Quantum-Classical Computing (HQCC) (a.k.a. Variational Quantum Eigensolver (VQE)) is often touted as one of the main algorithms of Quantum AI. In fact, Rigetti, a Silicon Valley company which for several years has provided cloud access to their superconductive quantum computer, has designed its services around the HQCC paradigm.

In this brief blog post, I will explain how HQCC can be understood in terms of quantum Bayesian networks. In the process, I will…

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Added by Robert R. Tucci on May 20, 2020 at 3:06pm — No Comments

Damn Pandemic: Epidemiological Models

After being confined for 2 months and hearing the word pandemic almost daily, seeing graphs, opinions, time lines and values that rise and fall, I became curious. Firstly, what is a pandemic? Is it the same as an epidemic? A plague? Was the plague an epidemic? What do epidemiologists study? Yes, they study a discipline called epidemiology.

 

What is epidemiology?

 

Epidemiology studies the distribution, frequency, relationships, predictions, and…

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Added by Luis Hidalgo Encinas on May 19, 2020 at 9:00pm — No Comments

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