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August 2016 Blog Posts (87)

Python: Getting Started with Data Science

This post was written by Dallin Akagi and Mark Steadman.

This short tutorial will not only guide you through some basic data analysis methods but it will also show you how to implement some of the more sophisticated techniques available today. We will look into traffic accident data from the National Highway Traffic Safety Administration and try to predict fatal accidents using state-of-the-art statistical learning techniques.  If you are…

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Added by Emmanuelle Rieuf on August 20, 2016 at 4:30pm — No Comments

Theory Development Using Symbols Rather than Quantities

In this blog, I will be considering theory developments from changes in methodology. But first I want to express an opinion on the significance of using numbers. A "number" represents an amplitude or magnitude: 5 pencils; 13 paperclips; 50 sheets of paper. The purpose of these numbers is to facilitate the counting of things that are presumably the same in a specific way: e.g. all 5 pencils are in fact pencils - for if 1 were an eraser, there would be 4 pencils and 1 eraser. The use of…

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Added by Don Philip Faithful on August 20, 2016 at 8:30am — No Comments

Analyzing crime in NYC: data, visuals and source code

Contributed by Chuan Sun. He takes the NYC Data Science Academy 12 week full time Data Science Bootcamp program from July 5th to September 23rd, 2016. This post is based on their first class project - the Exploratory Data Analysis Visualization Project, due on the 2nd week of the program. You can find the original…

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Added by NYC Data Science Academy on August 18, 2016 at 10:30am — No Comments

Machine Learning Becomes Mainstream: How to Increase Your Competitive Advantage



First there was big data – extremely large data sets that made it possible to use data analytics to reveal patterns and trends, allowing businesses to improve customer relations and production efficiency. Then came fast data analytics – the application of big data analytics in real-time to help solve issues with customer relations, security,…

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Added by Ronald van Loon on August 18, 2016 at 7:00am — No Comments

The 5 Hottest Data Science Blog Posts of the Summer

It’s been a rather quiet summer on Data Science Central with fewer blog posts being published than at other times of the year, but I guess it shouldn’t be too much of a surprise – DSC has had to compete against summer holidays, the Euro 2016 football tournament and the Rio 2016 Olympics.

Of the relatively few that have been published, there have been a few gems. At the time of writing, the 5 blog posts on this list have been read by almost 60,000 of you.

If you haven’t seen any…

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Added by Lee Baker on August 18, 2016 at 5:30am — No Comments

Training an AI Doctor - By Tyler Schnoebelen

Training an AI Doctor 

By Tyler Schnoebelen, August 17, 2016

Some of the earliest applications of artificial intelligence in healthcare were in diagnosis—it was a major push in expert systems, for example, where you aim to build up a knowledge base that lets software be as good as a human clinician. Expert systems hit their peak in the…

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Added by Leena Kamath on August 17, 2016 at 12:30pm — 1 Comment

Brexit: Why Projections Were Wrong

Shame on YouGov! Did their survey really miss the outcome of the Brexit consultation? Not quite. If you hit your finger while hammering a nail into the wall, do not blame the hammer.

The media circuit is responsible for having broadcasted inaccurate information. I must confirm that I am in no way linked to YouGov, the market research agency that supplied most media agencies with projections of the outcome results for the Brexit consultation in the UK, and this article…

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Added by Mirio De Rosa on August 16, 2016 at 10:00pm — 6 Comments

AI vs Deep Learning vs Machine Learning

Summary:  Which of these terms means the same thing:  AI, Deep Learning, Machine Learning?  Are you sure?  While there’s overlap none of these is a complete subset of the others and none completely explains the others.

 

Take this quiz.

Which of the following are substantially the same things?

A. AI

B. Deep Learning

C.  Machine Learning

(Select your answer)

1.  A and B

2.  B and C

3.  A and…

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Added by William Vorhies on August 16, 2016 at 9:00am — 9 Comments

Why Visualize Data?

If a picture is worth thousand words, then what about a neat data visualization? Displaying information in graphics to generate better insights is not a new phenomenon, but, with the advent of technology and increased access to data, it has become far more prominent. Once restricted to analysis of economics, finance, and science, data visualization has emerged as an industry of its own.

There are now multiple tools to visualize…

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Added by Surendran B on August 16, 2016 at 12:30am — No Comments

Walmart Competition: Trip Type Classification

Contributed by Joe EckertBrandon SchlenkerWilliam Aiken and Daniel Donohue. They took the NYC Data Science Academy 12-week full-time data science bootcamp program from Sep. 23 to…

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Added by Vincent Granville on August 15, 2016 at 8:00pm — No Comments

Predicting the Higgs-Boson Signal

Contributed by by  Arda KosarZi JinKyle Szela, …

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Added by NYC Data Science Academy on August 15, 2016 at 1:00pm — No Comments

Weekly Digest, August 15

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.

Announcement

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Added by Vincent Granville on August 13, 2016 at 8:30am — No Comments

7 Tips for Getting Your Colleagues Hooked On R

This post lays out some helpful advice for organizing and running an R demo at your organization. Seeing is believing so its best to demo the power of R yourself. Check out this post to get you started. Have more tips? I’d love to hear them!

1) Pitch them R

You know R is amazing and now it’s time to convince…

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Added by Jake Moody on August 12, 2016 at 10:00am — 2 Comments

Building a Recommendation System for the Cooper Hewitt Design Museum

The Arthur Ross Terrace & Garden at Cooper Hewitt, Smithsonian Design Museum. Photo: Agaton Strom Photography The Arthur Ross Terrace & Garden at Cooper Hewitt, Smithsonian Design Museum. Photo: Agaton Strom Photography[/caption]

Contributed by Belinda Kanpetch. She graduated from the NYC Data…
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Added by NYC Data Science Academy on August 12, 2016 at 10:00am — No Comments

5 Marketing Automation Tools That Leverage Data Science to Boost ROI

Return on Investment (ROI) is defined as the ratio of a return (benefit or net profit) over the investment of resources that generated this return. Both the return and the investment are typically expressed in monetary units, whereas the ROI is calculated as a percentage.

ROI formula:     (Return – Investment)/Investment

It’s typically expressed as a percentage, so multiply your results by 100.…

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Added by Amy Porras on August 12, 2016 at 2:30am — No Comments

The surprising relation between product managers and data scientists

Whenever we make a decision in business, we test a hypothesis, no matter if it is in product, marketing or sales, at the end we make assumptions that will guide our actions. When we say that we will implement the next feature, or run this campaign we make a hypothesis that this particular action will have some positive impact to what we have set as a goal. The goal could be our revenues, our signups, the time it takes for a customer to use the…

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Added by George Psistakis on August 11, 2016 at 1:30pm — No Comments

6 Ways Internet of Things is Already Changing Everything around Us

Connected devices, Smart City, home automation, e-health, Big Data ... In recent years, the concepts of communicating objects have multiplied. In reality, they are all one facet of the same upheaval - the Internet of Things.

Cars can be driven without a driver, TVs are going online, and heating systems are activated automatically to the arrival of the residents. The Internet is making many processes in daily life easier. The Internet of Things, or IoT, which enable devices to…

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Added by Jason Li on August 11, 2016 at 6:30am — No Comments

Improving Predictions with Ensemble Model

INTRODUCTION

“Alone we can do so little and together we can do much” - a phrase from Helen Keller during 50's is a reflection of achievements and successful stories in real life scenarios from decades. Same thing applies with most of the cases from innovation with big impacts and with advanced technologies world. The machine Learning domain is also in the same race to make predictions and classification in a more accurate way using so called ensemble method and it is…

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Added by Valiance Solutions on August 11, 2016 at 12:00am — No Comments

Book: Systems Analytics: Adaptive Machine Learning workbook

SYSTEMS Analytics title refers to a new development effort in the field of Machine Learning grounded firmly in Systems Theory; the subtitle, “ADAPTIVE Machine Learning”, captures the link to the current state of the art. My intention in writing this book is to bring mathematically trained graduates in engineering, physics, mathematics and…

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Added by Emmanuelle Rieuf on August 10, 2016 at 8:30am — No Comments

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