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Weekly Digest, November 12

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.

Announcements

  • Jump-start your career as a data scientist, data engineer, or analytics manager in…
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Added by Vincent Granville on November 11, 2018 at 6:30am — No Comments

Anatomy of an AI System

This article was written by Kate Crawford & Vladan Joler. Below is an extract, featuring the first three sections of this long article (21 sections total.) Link to the full article is provided at the bottom.…

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Added by Andrea Manero-Bastin on November 9, 2018 at 7:00pm — No Comments

Face Landmark Estimation Application

Face Landmark Estimation Application

After detecting a face in an image, as seen in the earlier post ‘Face Detection Application’, we will perform face landmark estimation. Face landmark estimation means identifying key points on a face, such as the tip of the nose and the center of the eye.…

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Added by Muhammad Rizwan on November 9, 2018 at 11:19am — No Comments

Artificial Intelligence Era Requires New Approaches to Create AI Talent

We live in the world of AI currently, and there is plenty of talk about what the future holds. With doubts over the future everywhere, one can predict that AI is soon going to be an imperative part of our lives. Considering the likely future impact of AI, there is a need to ensure that the right AI talent comes up and gets to the top to lead…

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Added by Ronald van Loon on November 8, 2018 at 9:45pm — No Comments

How Millennials Should View the World of Data Science

Many of my MBA students are perplexed about how much data science capabilities and skills they need in order to get hired.  It appears that in many job interviews, employers are looking for students who have both business subject matter as well as data science expertise. Here is an example of such a conversation:

MBA Student: I get lots of questions about my data science skills. I don't understand the need for that from me. I will never be as good as a…

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Added by Bill Schmarzo on November 8, 2018 at 1:38pm — No Comments

Thursday News: AI, Data Scientists Survey, Case Studies, Do you need a PhD, Impact of VC's

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

Resources

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Added by Vincent Granville on November 8, 2018 at 12:30pm — No Comments

AI technologies used in Robotics

 

 

Background

 

Robotics today is not the same as assembly line Robots of the industrial age because AI is impacting many areas of Robotics.

Specifically, AI is changing Robotics in two key areas

  1. Robots are becoming autonomous…
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Added by ajit jaokar on November 7, 2018 at 4:32am — No Comments

San Diego Water Pollution Map by Stations

I have been working with San Diego Water quality data project:

https://www.sandiegodata.org/2018/04/summer-water-quality-data-project/

Here are data sets:

https://data.sandiegodata.org/dataset?tags=water-project

Regretfully my complete works do not fit into the blog post (or even a few posts) because of a post…

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Added by Maiia Bakhova on November 6, 2018 at 11:46am — No Comments

Who are the Datascience Professionals? India vs US | Men vs Women

Introduction

This is an analysis of the Kaggle 2018 survey dataset. In my analysis I am trying to understand the similarities and differences between men and women users from US and India, since these are the two biggest segments of the respondent population. The number of respondents who chose something other than Male/Female is quite low, so I excluded that subset as well.

The complete code is available as a …

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Added by Anupama Rajaram on November 6, 2018 at 2:39am — 1 Comment

Is It Too Late For Me To Learn Coding?

The short answer is: "No."

Source: LEGO

I started teaching myself programming in my 40s, and I am a strong advocate that everyone should learn to code. Even if you have no intent to become a developer or a full-stack data scientist, coding teaches you a couple valuable…

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Added by Rafael Knuth on November 6, 2018 at 2:00am — 1 Comment

Useful Tips to Begin a Career in Data Science

Technological advancements along with the changing business environment have made a career in data science extremely lucrative to be pursued. However, it can be a little intimidating to learn data science. Especially, in the initial stages when there are so many techniques and tools to focus on.

Professionals planning to build a career in data science have different kinds of curiosities about what all they should or should not learn. And also about the relevance of skills like…

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Added by Yoey Thamas on November 5, 2018 at 8:41pm — No Comments

The Best Opportunities in AI for Data Scientists

Summary:  Looking for your next job in an early stage company but want to make sure your startup has staying power.  Follow the expert rankings by CB Insights that also show us the changing trends in how AI startups should be focusing their offerings.

 

Let’s…

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Added by William Vorhies on November 5, 2018 at 4:18pm — No Comments

How Lyft, Walmart, and Philips are using AI to transform their businesses

This article is a follow up to my previous one talking about the rise of Artificial Intelligence in an Enterprise. In this article, I will talk about how enterprises in Transportation, Retail and Healthcare are transforming themselves using AI.

Although I talk about specific enterprises here, the use cases are pretty generic and horizontal. The use…

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Added by Vimal N Suba on November 5, 2018 at 3:01pm — No Comments

The Ultimate R Cheatsheet

The Ultimate R Cheatsheet

We are developing a revolutionary new system for teaching Business Analysis with R (Business Analysis with R is a new course we are developing at Business Science University). The system is revolutionary for a number of reasons (we’ll get to these in a minute). The cornerstone of our teaching process is the Data Science with R Workflow that was originally taught by Hadley Wickham and Garrett Grolemund in the excellent…

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Added by Matt Dancho on November 5, 2018 at 3:30am — No Comments

Opinion: Is a PhD helpful for a data science career?

The answer to this question is not black and white, and also depends on where you live, what you did during your PhD program, how much time and money you spent on it, what kind of jobs you are interested in, and what other experience you have. You could say the same thing about earning an MBA instead.

If your PhD took place abroad as in my case, you may have not spent much money to earn it (you might even have been well paid.) Depending on your school, it might have been…

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Added by Vincent Granville on November 4, 2018 at 11:30am — 1 Comment

Weekly Digest, November 5

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.

Announcements

  • November 14th, 10:00am CST: Exclusive Insurance Nexus webinar: “…
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Added by Vincent Granville on November 4, 2018 at 7:00am — No Comments

Discrete Probabilities with R

Probability in general can be thought of as the chances of a particular event happening, say winning or loosing a game, the cliche’ example of  tossing a coin and what not.

When I say chance of an event, I mean the percentage of times that event would turn out if I were to do that experiment a large number of times.

Let us consider a box that contains 13 balls, out of which 5 are Blue and 8 are Red. What will be the probability of…

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Added by Savan Parmar on November 3, 2018 at 12:00am — No Comments

If data science is in demand, why is it so hard to get a job?

Another question recently posted on social networks. Below is my answer, with link to the original post. 

The main reason is the exponential growth of data science candidates, while the growth in job openings, even though exponential as well, is increasing at a lower pace than the number of applicants. In some ways, this is similar to the explosion of PhD people, while the number of jobs for these people is shrinking. One would wonder: why so many people want to get a PhD…

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Added by Vincent Granville on November 2, 2018 at 10:30am — No Comments

Keras Application for Pre-trained Model

In earlier posts, we learned about classic convolutional neural network (CNN) architectures (LeNet-5, AlexNet,…

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Added by Muhammad Rizwan on November 2, 2018 at 3:17am — No Comments

Unfolding Naïve Bayes from Scratch

This article was written by Aisha Javed. Below is a summary and table of content, for this long tutorial.

Whether you are a beginner in Machine Learning or you have been trying hard to understand the Super Natural Machine Learning Algorithms and you still feel that the dots do not connect somehow, this post is definitely for you!…

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Added by Andrea Manero-Bastin on November 1, 2018 at 5:30pm — No Comments

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