Model Types
Get an overview of machine learning model types.
We'll cover the following...
From linear regression to neural networks
Here’s a list of the ML models/algorithms we’ll likely use in production for various products:
Naive Bayes classifier
This algorithm naively considers every feature in our dataset as its own independent variable. So, it’s essentially trying to find associations probabilistically without having any assumptions about the data. It’s one of the simpler algorithms out there, and its simplicity actually is what makes it so successful with classification. It’s commonly used for binary values, such as trying to decipher whether or not something is spam.
Support vector machine (SVM)
This algorithm is also largely used for classification problems and will essentially try to split our dataset into two classes so that we can use it to group our data and try to predict where future data points will land along these major splits. If we do not see compelling groups between the data, SVMs allow us to add more dimensions to be able to ...
