Data Science Weekly Newsletter - Issue 180

Issue #180

May 4 2017

Editor Picks
 
  • Rethinking Design Tools in the Age of Machine Learning
    I would like to suggest that machine learning can help us to simplify design tools without limiting their expressivity, without taking creative control away from the designer.This may seem totally counter-intuitive...
  • Font Map
    Using artificial intelligence to surface new relationships across fonts...This interactive map of more than 750 fonts has been organized using machine learning....
  • The Simple, Economic Value of Artificial Intelligence
    I recently attended a very interesting talk , - Exploring the Impact of Artificial Intelligence: Prediction versus Judgment, - by University of Toronto professor Avi Goldfarb. The talk was based on recent research conducted with his UoT colleagues Ajay Agrawal and Joshua Gans...In their opinion, “the best way to assess the impact of radical technological change is to ask a fundamental question: How does the technology reduce costs? Only then can we really figure out how things might change.”...
 
 

A Message from this week's Sponsor:

 

 
 

Data Science Articles & Videos

 
  • Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing
    An effective (and often used) tool used to demonstrate that visualizing your data is in fact important is Anscome's Quartet....which is a set of four datasets, where each produces the same summary statistics (mean, standard deviation, and correlation)...we present, The Datasaurus Dozen, 13 datasets whom each have the same summary statistics (x/y mean, x/y standard deviation, and Pearson's correlation) to two decimal places, while being drastically different in appearance. This work describes the technique we developed to create this dataset, and others like it....
  • Soma Water Filters are Worthless: How I used R to win an argument
    Description: Armed with a fresh Soma filter (one which they touted was improved from their previous filter), I cancelled my subscription and set out to design an experiment to test my ability to distinguish between water types. And hopefully show both how I could tell the difference between filtered and unfiltered water, and potentially show empirically how bad the Soma filtered water tasted...
  • An AI wrote all of David Hasselhoff’s lines in a bizarre short film
    Last year, director Oscar Sharp and AI researcher Ross Goodwin released the stunningly weird short film Sunspring. It was a sci-fi tale written entirely by an algorithm that eventually named itself Benjamin. Now the two humans have teamed up with Benjamin again to create a follow-up movie, It's No Game, about what happens when AI gets mixed up in an impending Hollywood writers' strike. Ars is excited to debut the movie here, so go ahead and watch. We also talked to the film cast and creators about what it's like to work with an AI...
  • Explaining How a Deep Neural Network Trained with End-to-End Learning Steers a Car
    As part of a complete software stack for autonomous driving, NVIDIA has created a neural-network-based system, known as PilotNet, which outputs steering angles given images of the road ahead...The goal of the work described here is to explain what PilotNet learns and how it makes its decisions. To this end we developed a method for determining which elements in the road image most influence PilotNet's steering decision. Results show that PilotNet indeed learns to recognize relevant objects on the road...In addition to learning the obvious features such as lane markings, edges of roads, and other cars, PilotNet learns more subtle features that would be hard to anticipate and program by engineers, for example, bushes lining the edge of the road and atypical vehicle classes...
 
 

Jobs

 
  • Data Scientist - Knotch - NYC

    Knotch is a marketing intelligence company that enables CMOs to understand how their marketing efforts are impacting their audiences emotionally across every content distribution channel or geography in real time. Marketers use this unprecedented, real-time intelligence to optimize the creative and distribution of their marketing. We're based in New York and our client verticals include financial institutions, entertainment, and CPG.

    We’re a small team right now, so we’re looking for a teammate with a breadth of skills and a passion for learning. From ensuring data fidelity in our pipelines to building out full product features, and from preparing internal reports to giving polished client presentations, our ideal team member enjoys doing it all. In a typical day you may find yourself building out a deep net to classify web content, debugging a data discrepancy in our pipeline, or working with our Customer Success team on a custom analysis for a client. So, yeah, as our ideal team member, you’re as comfortable writing a simple SQL query to pull descriptive stats and making a beautiful bar chart as you are implementing a deep neural network, and you’d love to do both...
 
 

Training & Resources

 
  • A Beginner’s Guide to Neural Networks in Python and SciKit Learn 0.18
    The most popular machine learning library for Python is SciKit Learn. The latest version (0.18) now has built in support for Neural Network models! In this article we will learn how Neural Networks work and how to implement them with the Python programming language and the latest version of SciKit-Learn!...
  • A Better Way to Code - Introducing d3.express: the integrated discovery environment
    For the last eight years or so, I have been building tools for visualizing information. The most successful outcome of this effort has been D3, a JavaScript library...If we can’t eliminate coding, can we at least make it easier for humans, with our sausage fingers and finite-sized brains?...To explore this question I am building an integrated discovery environment called d3.express. It’s for exploratory data analysis, for understanding systems and algorithms, for teaching and sharing techniques in code, and for sharing interactive visual explanations...
  • Interesting Talks from PyData Amsterdam 2017
    This year, the PyData Amsterdam conference was held from the 7th to the 9th of April in Booking.com’s offices. The recordings of the talks were posted several days ago, and I decided to make the time to watch all of the talks, and do a short write-up with links to the talks I found the most interesting....
 
 

Books

 

 
 
P.S. Looking to hire a Data Scientist? Find an awesome one among our readers! Email us for details on how to post your job :) - All the best, Hannah & Sebastian
 
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