In machine learning and statistics, logistic regression is a tool used frequently to create models to summarize the probability of a certain class or event existing. This could be win or lose, pass or fail and many more. Logistic regression is often confused with linear regression, however, they have distinct differences. Linear regression is used to predict trends in data and create models through a “line of best fit”, also calculating sources of errors within the predictions.
I published Machine Learning article with video. Read the article here: https://medium.com/mlearning-ai/using-logistic-regression-in-machine-learning-with-python-66af0dd0135c
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