Terms and definitions from all courses

Kernel: An underlying core program, like Python
Keys: The shared points of reference between different dataframes


keys(): A dictionary method to retrieve only the dictionary’s keys


Keyword: A special word in a programming language that is reserved for a specific purpose and that can only be used for that purpose

L

Label encoding: Data transformation technique where each category is assigned a unique number instead of a qualitative value


Large Language Model (LLM): A type of AI algorithm that uses deep learning techniques to identify patterns in text and map how different words and phrases relate to each other
Leaf node: The nodes where a final prediction is made
learning_rate: In XGBoost, a hyperparameter that specifies how much weight is given to each consecutive tree’s prediction in the final ensemble
Left join: A way of combining data such that all of the keys in the left dataframe are included, even if they aren’t in the right dataframe


Len(): A function used to measure the length of strings Library: A reusable collection of code; also referred to as a “package”


Likelihood: The probability of observing the actual data, given some set of beta parameters
Line: A collection of an infinite number of points extending in two opposite directions
Linear regression: A technique that estimates the linear relationship between a continuous dependent variable and one or more independent variables
Linearity assumption: An assumption of simple linear regression stating that each predictor variable (X_i) is linearly related to the outcome variable (Y)
Link function: A nonlinear function that connects or links the dependent variable to the independent variables mathematically
Linkage: The method used to determine which points/clusters to merge