The elbow method is a technique used to find the optimal number of clusters (K) in k-means clustering, by identifying the “elbow” point on a graph of k-values and their corresponding within-cluster sum of squares (WCSS) values.
Ordinary Least Squares (OLS) regression is a technique used in linear regression to minimize the sum of squared differences between observed and predicted values, and obtain a straight line as close as possible to your data points.
Gaussian Naive Bayes is a classification technique used in machine learning based on the probabilistic approach and Gaussian distribution. Here’s a deep dive on how to use it in Scikit-Learn.
Adjusted R-squared is a modified version of R-squared that adjusts for predictors that do not contribute to predictive accuracy in a regression model. It can be a reliable measure of goodness of fit for multiple regression problems.
Asyncio is a Python library that allows us to write concurrent code using the async/await syntax. Learn how to use this library to write asynchronous code.
