I wanted to take a little bit of time to document what I have on my bookshelf as it relates to the data sciences, analytical methods, philosophy amongst others.
Methods, Techniques and Applications of Data Science
Common Anaconda-related Commands
This is asummary of pandas commands for which I sometimes forget the syntax and need a reminder.
This is a resource for Python procedures, scripts and one-liners that are useful and might be referenced at some frequency...
Geospatial Resources
This is a brief overview of Dask including how and why one might use it
We use an SSH tunnel to interact with a Jupyter Notebook in the cloud on our local machine.
We explore the best approach for using Git to persist and manage data science projects.
In this series, we are going to install the very useful Anaconda package as a fundamental part of your data science workbench.
We use Python here to grab some data from the Internet to conduct some analysis—we've got the code and a small business case here to help drive the point home.
We take some time to install this Relational Database Management System (RDMS) in our Data Science Workbench—and insert a few records so that you can begin persisting data in your own systems.
We are going to create a new user within the Ubuntu OS that is not the root user, but does have sudo (i.e. "root") privileges.
We are going to set up the foundation of our data science workbench in Linux Ubuntu —we will do this by using a virtual machine so we can do it all in the cloud.