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Data Science Weekly Newsletter
October 3, 2019

Editor's Picks

  • Building AI to inform people's fashion choices
    An AI system that proposes easy changes to a person’s outfit to make it more fashionable. Our Fashion++ system uses a deep image-generation neural network to recognize garments and offer suggestions on what to remove, add, or swap. It can also recommend ways to adjust a piece of clothing, such as tucking in a shirt or rolling up the sleeves...

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Data Science Articles & Videos

  • Teaching AI to plan using language in a new open-source strategy game
    Facebook AI has developed a new method of teaching AI to plan effectively, using natural language to break down complex problems into high-level plans and lower-level actions. Our system innovates by using two AI models — one that gives instructions in natural language and one that interprets and executes them — and it takes advantage of the structure in natural language in order to address unfamiliar tasks and situations. We’ve tested our approach using a new real-time strategy game called MiniRTSv2, and found it outperforms AI systems that simply try to directly imitate human gameplay...
  • Streamlit launches open-source ML application development framework
    Streamlit, a new ML startup from industry veterans who worked at GoogleX and Zoox, launched today with a $6 million seed investment and a flexible new open-source tool to make it easier for machine learning engineers to create custom applications to interact with the data in their models...
  • Visualizing a Neural Net Controlling an Interplanetary Spacecraft Trajectory
    I made this visualization from a research paper I wrote, Neural Network Based Optimal Control: Resilience to Missed Thrust Events for Long Duration Transfers. It's made by simulating a Mars to Earth Trajectory and letting the neural network control the spacecrafts thrust and flight path angle. It's made using Matlab...
  • How to Evaluate the Logistic Loss and not NaN trying
    A naive implementation of the logistic regression loss can results in numerical indeterminacy even for moderate values. This post takes a closer look into the source of these instabilities and discusses more robust Python implementations...
  • Hamiltonian Graph Networks with ODE Integrators
    We introduce an approach for imposing physically informed inductive biases in learned simulation models. We combine graph networks with a differentiable ordinary differential equation integrator as a mechanism for predicting future states, and a Hamiltonian as an internal representation. We find that our approach outperforms baselines without these biases in terms of predictive accuracy, energy accuracy, and zero-shot generalization to time-step sizes and integrator orders not experienced during training...
  • How much Math & Stats do I need on my Data Science resume?
    Do I need a strong math background to pursue a career as a data scientist? We see a lot of questions like this. Its hard when you're trying to break into the field to know exactly how much math & stats you need. And, part of the reason for that is that it really depends...


Create D3 Data Visualizations As Fast As You Can Sketch

You need to create a D3.js data visualization to communicate your insights. But... #d3BrokeAndMadeArt! This time, your data join appears to have broken and the JavaScript console shows an error you don't recognize. Last time, you got stuck trying to figure out how to make axes that didn't look like 3rd graded made them. It makes you want to strangle D3 with your bare hands. Just how steep does the D3 learning curve need to be?!
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  • Senior Data Scientist - TRANZACT - 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 Senior 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. Minimum 7 years of experience building predictive algorithms...
        Want to post a job here? Email us for details >>

Training & Resources

  • Stabilizing Generative Adversarial Network Training: A Survey
    The process of training GANs remains challenging, suffering from instability issues such as mode collapse and vanishing gradients. This survey summarizes the approaches and methods employed for the purpose of stabilizing GAN training procedure. We provide a brief explanation behind the workings of GANs and categorize employed stabilization techniques outlining each of the approaches. Finally, we discuss the advantages and disadvantages of each of the methods, offering a comparative summary of the literature on stabilizing GAN training procedure...


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Do more with your data! If you're looking to make your data skills stand out, then be sure to check out Manning's range of books and video courses.
They're offering 40% off everything in their catalog, so there's no better time to learn something new...
For a detailed list of books covering Data Science, Machine Learning, AI and associated programming languages check out our resources page

P.S., Enjoy the newsletter? Please forward it to your friends and colleagues - we'd love to have them onboard :) All the best, Hannah & Sebastian

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