The promise of data and analytics for product companies is that they can help you understand usage, and improve your ability to build, deploy, and service products to customers much more accurately and efficiently. In this post, we look at understanding the customer life cycle.
In this post, we’ll be talking through a few tools that help make data science teams more productive.
This article reviews the main options for free speech recognition toolkits that use traditional HMM and n-gram language models.
Travis and I discuss breaking down silos, the importance of effectively communicating about cutting-edge technology, and where Anaconda is going next.
In this post, we will explore some aspects of the train delay data we’ve been collecting from the Caltrain API.
One way to give back to the open source community that provides us with tools is to help others evaluate and choose those tools in a way that takes advantage of our experience. We offer this analysis, along with explanations of the various criteria upon which we based our decisions.
In this post we look at the three components you can use to determine your data strategy’s ROI.
In this post, Matt talks about using TensorFlow to detect true and false positives in our Caltrain work.
In this post we explore how data is changing the insurance industry, through the lens of auto insurance underwriting.