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August 2018 Blog Posts (93)

Weekly Digest, August 27

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.

Featured Resources and Technical Contributions 

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Added by Vincent Granville on August 25, 2018 at 3:30pm — No Comments

Four Types of Data Scientists

I wrote about this long ago (see here in 2014), and so did many other practitioners. This new post shows more maturity I think, a more coherent view about the various data scientist roles in the Industry (now that things are getting more clear for most hiring managers), and how these scientists interact between themselves and with other teams. It is also a short…

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Added by Vincent Granville on August 25, 2018 at 12:30pm — 2 Comments

The Artificial Neural Networks handbook: Part 1

I have written several articles on Artificial Neural Networks earlier but they were just random articles on random concepts. This series of articles will give you a detailed idea about Artificial neural networks and concepts related to it. The resources and references to all the…

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Added by Jayesh Bapu Ahire on August 24, 2018 at 9:00am — No Comments

Telecom: Enterprise Messaging is the New Black

Enterprises love messaging. There is no evidence in this world that can deny the obviousness of the fact that enterprises just love reaching out to their customers. Be it regarding new deals, a new promotion, or just to remind people about them, enterprises cannot stop themselves from reaching out to who they serve. These messages are expertly crafted for the end audience in mind, and they have a high rate of reaction. Gone are the days when email marketing…

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Added by Ronald van Loon on August 24, 2018 at 5:28am — No Comments

First Step to Become Data Scientist

Do you want to become a ‘Data Scientist’? If yes, then the first step is to understand the basic terms and their usage.

A – Brief History

Data Science is not a new field as the statisticians were doing the job even before the computer invention. Though, the evolution of modern computing technologies empowered statisticians to solve a wide variety of practical problems with heavy number crunching and massive data storage. The terms ‘knowledge…

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Added by Muhammad Rizwan on August 24, 2018 at 3:30am — No Comments

Silicon Valley Firms Make It Nearly 'Impossible' For Cambridge To Hire AI Staff

This article was written by Sam Shead.

US tech giants are making it "almost impossible" for the University of…

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Added by Kelly Quintana on August 23, 2018 at 9:33pm — No Comments

Demystifying Artificial Intelligence - Explained in One Picture

This article was written by Swami Chandrasekaran.

Click on picture to zoom in. Source:…

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Added by Kelly Quintana on August 23, 2018 at 9:30pm — No Comments

How do you identify an actual data scientist?

This question was recently posted on Quora, and generated a lot of answers. Here is mine:

What differentiates a real doctor from a fake doctor? What about one with no medical degree who cures himself and his family and friends, with better outcomes than official healthcare, for free, and does not call himself a doctor? …

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Added by Vincent Granville on August 23, 2018 at 12:56pm — No Comments

Thursday News: Spark, Python, Image Processing, ETL, AI, Statistical Tests, Watson

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

Technical Resources

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Added by Vincent Granville on August 23, 2018 at 9:30am — No Comments

Top 7 Data Science Use Cases in Healthcare

Medicine and healthcare is a revolutionary and promising industry for implementing the data science solutions. Data analytics is moving the medical science to a whole new level, from computerizing medical records to drug discovery and genetic disease exploration. And this is just the beginning.…

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Added by Igor Bobriakov on August 22, 2018 at 10:30am — No Comments

Prioritization Matrix:  Aligning Business and IT On The Big Data Journey

One key challenge to a successful Big Data journey is gaining consensus and alignment between the business and IT stakeholders in identifying the initial big data business use cases that 1) deliver sufficient value to the business, while 2) possessing a high probability of success.  One can find multiple business use cases where big data and advanced analytics can deliver compelling business value.  However, many of these use cases have a low probability of…

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Added by Bill Schmarzo on August 22, 2018 at 8:51am — No Comments

3 Stages of Creating Smart

Tomorrow’s market winners will win with the smartest products.  It’s not enough to just build insanely great products; winners must have the smartest products!” – Bill Schmarzo

Okay, that’s a pretty bold statement on my part (especially to challenge the famous Steve Jobs statement about building insanely great products), but then again I’m an analytics dude and think that analytics should be a part of every product and space – smart cities, smart cars, smart…

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Added by Bill Schmarzo on August 22, 2018 at 8:12am — No Comments

Watson – Time to Prune the ML Tree?

Summary:  IBM’s Watson QAM (Question Answering Machine), famous for its 2011 Jeopardy win was supposed to bring huge payoffs in healthcare.  Instead both IBM and its Watson Healthcare customers are rapidly paring back these projects that have largely failed to pay off.  Watson was the first big out-of-the-box commercial application in ML/AI.  Has it become obsolete?

  …

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Added by William Vorhies on August 21, 2018 at 10:51am — No Comments

Top 9 Data Science Use Cases in Banking

Using data science in the banking industry is more than a trend, it has become a necessity to keep up with the competition. Banks have to realize that big data technologies can help them focus their resources efficiently, make smarter decisions, and improve performance.

Here is a list of…

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Added by Igor Bobriakov on August 20, 2018 at 10:00am — No Comments

MATLAB toolbox on regime switching copula estimation and simulation

Hi all.

You may want to check out my code on regime switching copula models.The toolbox is designed to estimate the parameters of a regime switching copula model, assuming two regimes. Each regime can be described by any of the following five copulas:

  • t - copula
  • Gaussian Copula
  • Clayton Copula
  • Frank Copula
  • SJC copula

The correlation coefficient, rho, for the eliptical copulas and the copula parameter tau, for Clayton and…

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Added by Manthos Vogiatzoglou on August 20, 2018 at 12:00am — No Comments

Car robbery in São Paulo - Avoid places with less street lighting

Is there a relationship between car robbery and street lighting?

The last article was related to robbery and theft cars registered in the Police Department in the year of 2017. This article wants to check if there is a correlation between car robbery and less street lighting.

The Figure 1 bellow shows concentration of car's robbery per neighborhood. A neighborhood filled in black doesn't have any records. Soft yellow are neighborhood with less records, going up to orange dark…

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Added by Thiago Buselato Maurício on August 19, 2018 at 9:45am — No Comments

Can we use deliberate practise for learning to code #AI and #machinelearning

In this post, I explore if ideas of deliberate practise can be applied to teaching coding for Artificial Intelligence / Machine Learning

I am exploring these ideas in a free coding workshop/ meetups in London.

There is already a waiting list.

We may hold more workshops next year…

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Added by ajit jaokar on August 18, 2018 at 10:30pm — 7 Comments

Weekly Digest, August 20

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.

Featured Resources and Technical Contributions 

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Added by Vincent Granville on August 18, 2018 at 5:30pm — No Comments

Understanding Type I and Type II Errors

Reviving from the dead an old but popular blog on Understanding Type I and Type II Errors

I recently got an inquiry that asked me to clarify the difference between type I and type II errors when doing statistical testing.  Let me use this blog to clarify the difference as well as discuss the potential cost ramifications of type I and type II errors. I have also provided some examples at the end of the blog[1]

In statistical test theory, the…

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Added by Bill Schmarzo on August 18, 2018 at 3:35pm — 2 Comments

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