Tutorials

In Part 1, we covered the basics of doing text mining in R by selecting data, preparing it, cleaning, then performing various operations on...

TensorFlow has picked up a lot of steam over the past couple of months, and there's been more and more interest in learning how...

Language modeling is defining a joint probability distribution over a sequence of tokens (words or characters). Considering a sequence of tokens fx1; :::; xT...

In machine learning, a generative model is one that captures the observable data distribution. The objective of deep neural generative models is to disentangle...

Torch is a scientific computing framework built on top of Lua. The nn package and the ecosystem around it provide a very powerful framework...

In a previous two-part post series on Keras, I introduced Convolutional Neural Networks(CNNs) and the Keras deep learning framework. We used them to solve...

In this two-part post series, we are solving a Natural Language Processing (NLP) problem with Keras. In Part 1, we covered the problem and...

In this post, we are going to look at how to use the Firebase real-time database, along with an example. Here we are writing...

In this blog post, we begin with a simple classification task that the reader can readily relate to. The task is a binary classification...

In this article, we will begin to see the real power and flexibility the Warehouse Builder provides us for loading a data warehouse. When...