Here you can learn the fundamental python commands for visualising ocean data as well as data pre-processing techniques (a crucial step in ML processes). You'll learn the fundamentals of using NumPy, pandas, Xarray, eofs (for using empirical orthogonal functions), and machine learning libraries like SciPy in Python. We used Argo data as well as some data from the APDRC.

About Argos: Each Argo probe is a self-contained profiling float that can drift freely. After 9 to 10 days of free drift at a parking depth of about 1000m, a typical Argo float sinks to 2000m and then returns to the surface while profiling measuring pressure, temperature, and salinity. Argopy Libary has been used to fetch the Argo dataset.

Note: Please note that I haven't uploaded all my codes and figures till now for some reason, but I will upload them ASAP.