The Old: Exploring ML
Explore the foundational concepts of traditional machine learning, including key statistical models like linear regression, support vector machines, and decision trees. Understand the historical development and mathematical principles behind these models, and learn how ML processes data to predict and classify real-world phenomena effectively.
We'll cover the following...
Traditional ML models
ML models attempt to create some representation of reality in order to help us make some sort of data-driven decision. Essentially, we use mathematics to represent some phenomenon that’s happening in the real world. ML essentially takes mathematics and statistics to predict or classify some future state. The paths diverge in one of two ways. The first group lies with the emergence of models that continue to progress through statistical models, and the second group lies with the emergence of models that try to mimic our own natural neural intelligence. Colloquially, these are referred to as traditional ML and DL models.
