In Data Science the 80/20 rule means spending 80% of time preparing data and 20% actually using it. With so many organisations looking to use Data Science/Machine Learning/AI making more efficient use of time is vital.
Another dimension of this problem is the volume of data to be processed. Better input leads to better models, but for analysts and scientists access to the full data set isn't always practical.
This session will explore how to use Db2 to enhance data exploration using built-in capabilities such as Principal Component Analysis and K-means clustering, and apply it to the entire data set. We'll also cover using
Db2 with languages such as Python, and common tools such as Pandas.