Image Processing in Python
In this post, we use a Jupyter Notebook go over the steps for creating a proof of concept for the image processing piece of our Caltrain work.
Archive for the ‘R&D’ Category
Introduction to Trainspotting
In this post we’ll start looking at the nuts and bolts of making our Caltrain work possible: image processing, video analysis, and image recognition.
Noteworthy Links: Social Media Edition
In this post we share some links to interesting work being done with social media data.
Talking About the Caltrain
On May 6th, SVDS hosted an Open Data Science Conference (ODSC) Meetup in our Mountain View headquarters. Data Engineer Harrison Mebane and Data Scientist Christian Perez presented on our Caltrain project.
IoT and Resilient Systems
We believe there are clearly some compelling value propositions that come from integrating the visibility from the IoT into applications that help understand and manage the state of complex systems. With the internet of things, the more things, really, the merrier.
Analyzing Caltrain Delays: What We Can Learn
In this post, we will explore some aspects of the train delay data we’ve been collecting from the Caltrain API over the past few months. The goal is to get our heads into the data before setting off on building a prediction model.
How to Choose a Data Format
It’s easy to become overwhelmed when it comes time to choose a data format. In this post Silvia gives you a framework for approaching this choice, and provide some example use cases.
How Do You Build a Data Product?
Data products are the reason data scientists are lately treated like rockstars. Along the way at SVDS, we’ve learned a few things about data products, which we shared as we told the story of the Caltrain Rider app.
Valuing Data is Hard
This article is the first in a series that I will be posting on the topic of thinking about data as an intangible asset, and how to value it as such.