Data Science Weekly Newsletter - Issue 229

Issue #229

Apr 12 2018

Editor Picks
 
  • Differentiable Plasticity: A New Method for Learning to Learn
    To give our artificial agents similar abilities, Uber AI Labs has developed a new method called differentiable plasticity that lets us train the behavior of plastic connections through gradient descent so that they can help previously-trained networks adapt to future conditions...
  • 70% Engineering Estimates
    I just made a prediction training targeted at engineers and data scientists. The idea is to train people in the same way engineers and scientists train machine learning systems: by having them predict known outcomes of interest. The goal is to improve people's ability to make judgement based predictions about impact and cost (when little data is available)...
 
 

A Message from this week's Sponsor:

 

 
Join the Premier Machine Learning Conference

Since 2009, Predictive Analytics World, Las Vegas – June 3-7, 2018, is the leading cross-vendor conference covering the commercial deployment of machine learning, deep learning and predictive analytics. Featuring five parallel events on Business, Financial, Healthcare, Manufacturing, and Deep Learning across seven tracks, 150+ International Speakers, 150+ cutting edge sessions, 11 workshops, Mega-PAW has something for everyone. Connect in-person with leading experts and hear data scientists from companies such as Uber, Google, Caterpillar, Dell, Microsoft, State Street, Capital One, Northern Trust, Turner, Comcast, Shell, Verizon, Monsanto and many more.

10% discount for DSW readers using code DSW10 when registering.

   
 

Data Science Articles & Videos

 
  • Deep Learning for Radars
    Radars have a long story. They used to be large, expensive and available for military only. Nowadays, many cars have a bunch of single-chip radars embedded into bumpers to enable autonomous emergency braking, cross-traffic alerts or lane change assist...
  • DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills
    A longstanding goal in character animation is to combine data-driven specification of behavior with a system that can execute a similar behavior in a physical simulation, thus enabling realistic responses to perturbations and environmental variation. We show that well-known reinforcement learning (RL) methods can be adapted to learn robust control policies capable of imitating a broad range of example motion clips, while also learning complex recoveries, adapting to changes in morphology, and accomplishing user-specified goals...
  • Transforming data with zeros
    I’m currently working with a hydrologist and he raised a question that occurs quite frequently with real data — what do you do when the data look like they need a log transformation, but there are zero values?...
  • Using AWS DeepLens to translate American Sign Language to speech
    ASLens uses AWS DeepLens to capture video of a person signing in American Sign Language (ASL). Then it runs a deep learning model (built with Amazon SageMaker) against each frame. When a letter from the ASL alphabet is recognised, AWS DeepLens plays the audio of that letter (using an MP3 file generated using Amazon Polly). ASLens runs locally on the AWS DeepLens, so an internet connection is not required, eliminating bandwidth issues and increasing speed....

 

Jobs

 
  • Data Scientist - VillageCare - NYC
    VillageCare is a community-based, non-profit organization serving people with chronic care needs, as well as seniors and individuals in need of continuing care and rehabilitation services.

    The Data Scientist will support our Provider Relations team with insights gained from analyzing company data. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action...
 
 

Training & Resources

   
 

Books

 

  • Data Science from Scratch: First Principles with Python

    "It does three things superbly: covers the basic low level tools of a data scientist (the "from scratch" part), gives a great overview of useful Python programming examples for those new to Python, and gives an amazingly succinct yet high level overview of the mathematics and statistics required for data science..."


    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
 
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