This post is the fourth in a series on deep learning using Keras. We've already looked at dense networks with category embeddings, convolutional networks, and recommender systems. For this installment we're going to use recurrent…
In this post we'll continue the series on deep learning by using the popular Keras framework to build a recommender system. This use case is much less common in deep learning literature than things like image classifiers or text g…
In my last post, I kicked off a series on deep learning by showing how to apply several core neural network concepts such as dense layers, embeddings, and regularization to build models using structured and/or time-series data. In…
This post marks the beginning of what I hope to become a series covering practical, real-world implementations using deep learning. What sparked my motivation to do a series like this was Jeremy Howard's awesome fast.ai courses [h…
Learning data science is a process of exploration. It involves continually expanding the surface area of concepts and techniques that you have at your disposal by learning new topics that build on or share a knowledge base with th…