Data Modeling includes various techniques for modeling the data for storage in databases.
This competency area includes estimating probabilities using Bayesian modeling, understanding Linear regression, Logistic regression, and predicting labels to name a few.
- Estimate probabilities using Bayesian modeling - Take a series of observations and estimate the prevalence of each data type using data science libraries.
- Linear regression - Predict and determine the linear relationship between independent and dependent variables using data science libraries.
- Logistic regression - Predict and determine the probability of a binary variable using data science libraries.
- Separate features into different domains - Using a support vector classifier, find a hyperplane that best separates features into different domains using data science libraries.
- Predict labels using decision tree classifier - Predict the class or value of a target variable using simple decision rules and data science libraries.