Analyzing Sentiment in Caltrain Tweets
As a first step to using Twitter activity as one of the data sources for train prediction, we start with a simple question: How do Twitter users currently feel about Caltrain?
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Ben Everson
Ben has a background in computational biophysics, where he leveraged complex bioinformatic data to build functional proteins from scratch. He is excited about applying advanced mathematical modeling and machine learning techniques to test hypotheses and deliver elegant solutions to the most difficult problems.
Recent Posts
Getting Started with Predictive Maintenance Models
In this post, we’ll start to develop an intuition for how to approach the remaining useful life (RUL) estimation problem and take the first steps in modeling RUL.
Predictive Maintenance for IoT
In this post, we’ll cut through some of the ambiguity around IoT applications, and introduce an example data science problem relevant to the IoT world.
Driving Product Engagement with User Behavior Analytics
In this post, we will look at driving product engagement with behavioral data, as well as building an integrated analytical environment.
Data-Driven User Engagement
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.