This morning I had the opportunity to chat with software engineers and data scientists at the AI Dev World Conference on a topic I just happen to be v...
We use data science — machine learning, natural language processing, etc. in Pinpoint to correlate data from all the tools used to build software to unlock actionable insights, make recommendations on how to improve execution, predict risks, and forecast work effort.
Data Science is often written off as a “black box” due to its vagueness. Here at Pinpoint, we strive to be transparent in everything we do, including “showing our work” with customized explanations for each metric or prediction and sharing how we build our projects.
Below I am sharing what libraries are used in our work in an effort to continue that transparency. We don’t use any third-party applications that supplement our analyses, besides our code editor, VSCode. All of the below libraries are based in Python.
The below libraries are our go-to’s and are widely used within the industry.
Here are other packages heavily-used in our work and deserve much more kudos in the industry.
I recommend checking out the below articles for more on our data science infrastructure.
Data Scientist, Team Lead
This morning I had the opportunity to chat with software engineers and data scientists at the AI Dev World Conference on...
Data science is fundamental to Pinpoint’s application. But, like most startups, we are still in the process of building ...