Many datasets have location information – longitudes and latitudes. Census data, traffic data, landmarks data, etc. If we have data associated with locations, it may be very useful to display the locations on a map. This would not only allow us to visualize the locations of interest, but also follow trends and draw insights.
I have recently started learning about analyzing and modeling audio signals using Python.
I analyzed the texts from the infamous Harry Potter book series using natural language processing (NLP) techniques in Python.
Can you relate?
I recently completed the 12-week Metis Data Science bootcamp in Chicago. This post is focused on my capstone project, which is a client based project for DigiatlGlobe, a commercial vendor for satellite imagery. It involves analyzing DigitalGlobe’s high resolution satellite data to obtain a detailed representation of land use on Earth.
A visualization of topics found from the Harry Potter book series using SciKit-Learn LDA topic modeling techniques.
The ability to predict taxi ridership could present valuable insights to city planners and taxi dispatchers in answering questions such as how to position cabs where they are most needed, how many taxis to dispatch, and how ridership varies over time.