How to Extract Useful Information from Data
Regardless of how you use data science, most of us have a common goal – extracting useful information from data. In this episode of the Data Science Roadshow, we look at models and machine learning. Models used in data science are drawn from a variety of disciplines, in particular, statistics, mathematics, data mining, and machine learning. There are similarities and differences but considerable overlap. We also delve into machine learning, describing the different types of learning emulated in machine learning algorithms. We include an overview of IMSL, a collection of data science algorithms offered in several native languages.
Interested in Learning More About Data Science?
Watch the rest of the Data Science Roadshow:
- Part 1: What is Data Science?
- Part 3: Data Science for Volatility Forecasting
- Part 4: Data Science for the Transportation Problem
See how IMSL Numerical Libraries allows you to address complex problems quickly with a variety of readily-available algorithms.