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.

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
Analyzing Advertising Data and Making Predictions using Logistic Regression.ipynb		Analyzing Advertising Data and Making Predictions using Logistic Regression.ipynb
Analyzing the Titanic Dataset using Logistic Regression.ipynb		Analyzing the Titanic Dataset using Logistic Regression.ipynb
License.md		License.md
Linear Regression - Comparing Housing Costs.ipynb		Linear Regression - Comparing Housing Costs.ipynb
Mobile App Regression Analysis Demo.ipynb		Mobile App Regression Analysis Demo.ipynb
README.md		README.md
USA_Housing.csv		USA_Housing.csv
advertising.csv		advertising.csv
titanic_train.csv		titanic_train.csv

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