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Linear and Logistic Regression Analysis

Some examples of Linear and Logistic Regression Analysis using scikit-learn and tensorflow.

  • Analyzing click effectiveness of Advertising Data in a web app (Logistic Regression)
    Working with a fake advertising data set that indicates whether or not a particular internet user clicked on an Advertisement, we will try to create a model that will predict whether or not they will click on an ad based off the features of that user.

  • Titanic Dataset Analysis (Logistic Regression) This is mostly a demonstration of cleaning up data to prepare it for a Logistic Regression and preparing a confusion matrix.

  • Comparing Housing Costs (Linear Regression) Analyzing the 1970s Boston Housing dataset in scikit-learn

  • Mobile App Analysis (Linear Regression)
    The scenario is this: an eCommerce company sells clothing online but they also have in-store style and clothing advice sessions. Customers come in to the store, have sessions/meetings with a personal stylist, then they can go home and order either on a mobile app or website for the clothes they want.

The jupyter notebooks can be opened in Github by clicking on the notebook file. Might need a refresh to load depending on your browser.

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