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…
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. I…
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,…
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 t…
Sometimes it pays to go back to basics. Data science is a massive, complicated field with seemingly endless topics to learn about. But in our rush to learn about the latest deep learning trends, it's easy to forget that there are…