Data Science Weekly Newsletter - Issue 283

Issue #283

Apr 25 2019

Editor Picks
 
  • A Recipe for Training Neural Networks
    Some few weeks ago I posted a tweet on “the most common neural net mistakes”, listing a few common gotchas related to training neural nets. The tweet got quite a bit more engagement than I anticipated (including a webinar :)). Clearly, a lot of people have personally encountered the large gap between “here is how a convolutional layer works” and “our convnet achieves state of the art results”. So I thought it could be fun to brush off my dusty blog to expand my tweet to the long form that this topic deserves...
  • MuseNet
    We’ve created Musenet, a deep neural network that can generate 4-minute musical compositions with 10 different instruments, and can combine styles from country to Mozart to the Beatles...
 
 

A Message from this week's Sponsor:

 

 
Rev Summit for Data Science Leaders | May 23-24, 2019

In a recent post, Derwen’s Paco Nathan reveals themes for the upcoming Rev Summit and previews what he is most excited for at the conference.

Come to New York City on May 23–24 to learn from data science teams and leaders at Netflix, Slack, Stitch Fix, Domino Data Lab, Microsoft, Dell, Red Hat, Google, Turner Broadcasting System, Humana, Workday, Lloyds Banking Group, BNP Paribas Cardif, and many others about topics like:
  • How to develop a mature, sustainable data science practice with tangible impact on the business.
  • Specific steps the world’s leading model-driven organizations took to elevate data science internally.
  • Best practices, methodologies, and technologies for amplifying collaboration across teams.
Use exclusive promo code DSW_REV to get $100 off your order!
 
     
 

Data Science Articles & Videos

 
  • How Artificial Intelligence Is Changing Science
    The latest AI algorithms are probing the evolution of galaxies, calculating quantum wave functions, discovering new chemical compounds and more. Is there anything that scientists do that can’t be automated?...
  • How to hide from the AI surveillance state with a color printout
    AI-powered video technology is becoming ubiquitous, tracking our faces and bodies through stores, offices, and public spaces. In some countries the technology constitutes a powerful new layer of policing and government surveillance. Fortunately, as some researchers from the Belgian university KU Leuven have just shown, you can often hide from an AI video system with the aid of a simple color printout...
  • Evaluating the Unsupervised Learning of Disentangled Representations
    In "Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations" (to appear at ICML 2019), we perform a large-scale evaluation on recent unsupervised disentanglement methods, challenging some common assumptions in order to suggest several improvements to future work on disentanglement learning. This evaluation is the result of training more than 12,000 models covering most prominent methods and evaluation metrics in a reproducible large-scale experimental study on seven different data sets...
  • Intelligible speech synthesis from neural decoding of spoken sentences
    Decoding speech from neural activity is challenging because speaking requires extremely precise and dynamic control of multiple vocal tract articulators on the order of milliseconds. Here, we designed a neural decoder that explicitly leverages the continuous kinematic and sound representations encoded in cortical activity5,6 to generate fluent and intelligible speech. A recurrent neural network first decoded vocal tract physiological signals from direct cortical recordings, and then transformed them to acoustic speech output...
  • Free-form Video Inpainting with 3D Gated Convolution & Temporal PatchGAN
    In this paper, we introduce a deep learning based free-form video inpainting model, with proposed 3D gated convolutions to tackle the uncertainty of free-form masks and a novel Temporal PatchGAN loss to enhance temporal consistency. In addition, we collect videos and design a free-form mask generation algorithm to build the free-form video inpainting (FVI) dataset for training and evaluation of video inpainting models. We demonstrate the benefits of these components and experiments on both the FaceForensics and our FVI dataset suggest that our method is superior to existing ones...
  • Vue.ai raises $17 million for AI-driven retail products
    Vue.ai, which in three years has experienced 200 percent annual revenue growth and seen household names like Macy’s, Levi’s, Diesel, Thredup, Tata, and Mercadolibre join its customer base, offers a suite of seven products designed to automate management and merchandising processes and personalize omnichannel customer experiences. In an internal study, the company claims that online shoppers spent upwards of 72 minutes on websites where its software was deployed, compared with 25 minutes on sites without it...
  • How your data scientists become bottlenecked
    Data scientists are worth their weight in gold but they can become ineffective and bottlenecked if they don’t know the customer, the business problem, or the data itself...
 
 

Jobs

 
  • Data Scientist - TRANZACT - Fort Lee, NJ or Raleigh, NC

    Tranzact is a fast paced, entrepreneurial company offering a well-rounded suite of marketing solutions to help insurance companies stay ahead of the competition. The Data Scientist will be solving the toughest problems at Tranzact by using data. More specifically, responsible for gathering data, conducting analysis, building predictive algorithms and communicating findings to drive profitable growth and performance across Tranzact. Must have a strong grasp on the data structure, business needs, and statistical and predictive modeling...

        Want to post a job here? Email us for details >> team@datascienceweekly.org
 

 

Training & Resources

 
  • ML in KSQL
    Exploiting KSQL stream transformation and user-defined functions to deploy realtime machine learning models...
 
 

Books

 

  • The Joy of x: A Guided Tour of Math, from One to Infinity

    "Delightful . . . easily digestible chapters include plenty of helpful examples and illustrations. You'll never forget the Pythagorean theorem again!"...


    For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page.
     

     
    P.S., Want to reach our audience / fellow readers? Consider sponsoring - grab a spot now; first come first served! All the best, Hannah & Sebastian
 
Sign up to receive the Data Science Weekly Newsletter every Thursday

Easy to unsubscribe. No spam — we keep your email safe and do not share it.