From the course: Machine Learning with Python: Logistic Regression

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How to explore data for logistic regression in Python

How to explore data for logistic regression in Python - Python Tutorial

From the course: Machine Learning with Python: Logistic Regression

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How to explore data for logistic regression in Python

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- [Speaker] Logistic regression is one of the simplest and most commonly used classification approaches in machine learning. It is a supervised machine learning approach that allows us to model the relationship between a set of predictors and the probability of a categorical response. In this video, you will learn how to import and explore data prior to building a logistic regression model in Python. Note that this video is the first in the four video sequence that also teaches you how to prepare data, train a logistic regression model, evaluate the model, and interpret the model in Python. I would also like to highlight that the Python packages we use in these four tutorials Pandas, Matplotlib, Seaborn, NumPy and SKLearn have all been pre-installed for you as part of your code spaces environment. Let's get started. The first thing we're going to do is import our data. Before we import our data, we must first…

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