Data Science Weekly Newsletter - Issue 232

Issue #232

May 3 2018

Editor Picks
 
  • Data Science for Startups: Introduction
    I recently changed industries and joined a startup company where I’m responsible for building up a data science discipline. While we already had a solid data pipeline in place when I joined, we didn’t have processes in place for reproducible analysis, scaling up models, and performing experiments. The goal of this series of blog posts is to provide an overview of how to build a data science platform from scratch for a startup, providing real examples using Google Cloud Platform (GCP) that readers can try out themselves...
  • WaveGAN Demo
    This is a demo of our WaveGAN method trained on drum sound effects (paper, code). All drum sounds are synthesized in browser by a neural network...
 
 

A Message from this week's Sponsor:

 

 
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Data Science Articles & Videos

 
  • AI in the UK: ready, willing and able? [PDF]
    The United Kingdom's House of Lords Select Committee has released its report on the UK's AI strategy. The almost two-hundred page report, AI in the UK: ready, willing and able? covers issues ranging from how to design AI, how to develop it, how to work with it, and how to engage with it...
  • Command Line Tricks For Data Scientists
    For many data scientists, data manipulation begins and ends with Pandas or the Tidyverse. In theory, there is nothing wrong with this notion. It is, after all, why these tools exist in the first place. Yet, these options can often be overkill for simple tasks like delimiter conversion...
  • TensorFlow Lite for iOS - Coding TensorFlow
    In this episode of Coding TensorFlow, Laurence Moroney, Developer Advocate for TensorFlow at Google, talks us through how TensorFlow Lite works on iOS. You'll see how to deploy a trained model to an iOS App, and how you can run inference with it, using C++ called from a Swift App...
  • An Introduction to Deep Learning for Tabular Data
    There is a powerful technique that is winning Kaggle competitions and is widely used at Google (according to Jeff Dean), Pinterest, and Instacart, yet that many people don’t even realize is possible: the use of deep learning for tabular data, and in particular, the creation of embeddings for categorical variables...

 

Jobs

 
  • Director of Data Science - Fair Trade Certified - Oakland, CA
    Fair Trade USA's newly formed Data Team works with departments across the organization to collect, manage, analyze and share data about Fair Trade USA’s business and the impact of our work. The organization is committed to being excellent stewards of our data while working quickly to create meaningful data insights that can be used to evaluate the effectiveness of our programs and deliver supply chain insights to our partners. The Director of Data Science will lead a team of 7 data practitioners at Fair Trade USA...
 
 

Training & Resources

 
  • Flatten A PyTorch Tensor
    Learn how to flatten A PyTorch Tensor by using the PyTorch view operation, via a screencast video and full tutorial transcript...
  • Announcing Open Images V4
    Today, we are happy to announce Open Images V4, containing 15.4M bounding-boxes for 600 categories on 1.9M images, making it the largest existing dataset with object location annotations...
 
 

Books

 

 
 
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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