An introduction to the Dirichlet process and its applications

Curated list of awesome GAN applications and demo. Contribute to nashory/gans-awesome-applications development by creating an account on GitHub.

Yuan Huang is an Insight alum from the Summer 2017 session of Insight Data Science in New York. Yuan is completing a PhD in Computational…

Check out Gitbub Repo for instructions and examples: https://goo.gl/LbVVPh
Also take a look at the Deep Lattice Networks publication for mathematical details: https://goo.gl/REE6cb

Maya Gupta, Seungil You and Jan Pfeifer introduce TensorFlow Lattice. TensorFlow…

Contribute to lol-category development by creating an account on GitHub.

tensorflow - Computation using data flow graphs for scalable machine learning

Hello world. This tutorial is a gentle introduction to building modern text recognition system using deep learning in 15 minutes. It will teach you the main ideas of how to use <a href="https://keras.io/" target="_blank">Keras</a> and <a href="https://supervise.ly/"…

High level network definitions with pre-trained weights in TensorFlow - taehoonlee/tensornets

How neural networks build up their understanding of images

Update: Part II is available here.

Posted by Michael Ringgaard, Software Engineer and Rahul Gupta, Research Scientist Until recently, most practical natural language understan...

News and insights on Google platforms, tools, and events.

Distributed deep learning allows for internet scale dataset sizes, as exemplified by many huge enterprises. This blog post demonstrates how an organization of any size can leverage distributed deep learning on Spark thanks to the Qubole Data Service (QDS).

An introduction to neural networks learning

The article is about Manhattan LSTM (MaLSTM) — a Siamese deep network and its appliance to Kaggle’s Quora Pairs competition. I will do my…

While scaling images in GIMP in the Quality section I was prompted to choose one of the following interpolations:
None
Linear
Cubic
Sinc(Lanczos3)
What is the difference between these and which o...

Text summarization is the problem of creating a short, accurate, and fluent summary of a longer text document. Automatic text summarization methods are greatly needed to address the ever-growing amount of text data available online to both better help discover…