No Coding Required: Training Models with Ludwig, Uber’s Open Source Deep Learning Toolbox

No Coding Required: Training Models with Ludwig, Uber’s Open Source Deep Learning Toolbox

  • June 28, 2019
Table of Contents

No Coding Required: Training Models with Ludwig, Uber’s Open Source Deep Learning Toolbox

Uber AI’s Piero Molino discusses Ludwig’s origin story, common use cases, and how others can get started with this powerful deep learning framework built on top of TensorFlow. Machine learning models perform a diversity of tasks at Uber, from improving our maps to streamlining chat communications and even preventing fraud. In addition to serving a variety of use cases, it is important that we make machine learning as accessible as possible for experts and non-experts alike so it can improve areas across our business.

In this spirit, we built Ludwig, an open source, deep learning toolbox built on top of TensorFlow that allows users to train and test machine learning models without writing code. To explain how this powerful framework works, Piero Molino, Ludwig creator and Uber AI senior research scientist, discusses Ludwig’s origin story, common use cases, and how others can get started with the software: Interested in learning more about Ludwig and AI at Uber? Check out the Ludwig repo and keep up-to-date with other projects Uber AI by subscribing to the Uber Engineering Newsletter!

Special thanks to Piero Molino, Wayne Cunningham, Stan Yee, Seamus Strahan-Malik, Deidre Locklear, Robert Brent Wilson, Blake Henderson, and Doug Rae for their contributions to this video.

Source: uber.com

Tags :
Share :
comments powered by Disqus

Related Posts

Creating Bitcoin trading bots that don’t lose money

Creating Bitcoin trading bots that don’t lose money

In this article we are going to create deep reinforcement learning agents that learn to make money trading Bitcoin. In this tutorial we will be using OpenAI’s gym and the PPO agent from the stable-baselines library, a fork of OpenAI’s baselines library. If you are not already familiar with how to create a gym environment from scratch, or how to render simple visualizations of those environments, I have just written articles on both of those topics.

Read More
Hash Your Way To a Better Neural Network

Hash Your Way To a Better Neural Network

The computer industry has been busy in recent years trying to figure out how to speed up the calculations needed for artificial neural networks—either for their training or for what’s known as inference, when the network is performing its function. In particular, much effort has gone into designing special-purpose hardware to run such computations. Google, for example, developed its Tensor Processing Unit, or TPU, first described publicly in 2016.

Read More
Detecting malaria with deep learning

Detecting malaria with deep learning

Artificial intelligence (AI) and open source tools, technologies, and frameworks are a powerful combination for improving society. ‘Health is wealth’ is perhaps a cliche, yet it’s very accurate! In this article, we will examine how AI can be leveraged for detecting the deadly disease malaria with a low-cost, effective, and accurate open source deep learning solution.

Read More