In this post you learn how to build a cross-platform application exposing real-time model fitting and business prediction as a RESTFul service using reactive Python.
The premise of denoising images is very useful and can be applied to images, sounds, texts, and more. While deep learning is possibly not the best approach, it is an interesting one, and shows how versatile deep learning can be.
In this post you are going to perform unit testing with Sails, taking advantage of Mocha, Chai and Instanbul.
Learn how to use the Blocks library with a deep learning example.
In this post, we will mostly focus on the tools gap, and how to bridge that gap in a Node application with Docker.
This post introduces you to how to construct your own network model on Chainer.
In this post you learn about the advantage of using KeyStoneJS and the community that helped the author become a committer for that community.
In this post you are going to learn how to use Python to create a custom progress bar that will run in your very own Slack channel.
In this post you achieve performance close to human level performance using Keras. You also improved the accuracy of the model using an augmentation of the training data.
Learn how Swift's playgrounds embody that friendliness by modernizing the concept of a REPL