Within the scope of this chapter, we've prepared a Python module (simple and unprepared to use in production) that implemented three different models for linear regression. Even though linear regression is often inappropriate for time-series analysis, this method is well-known and easy to understand, so it serves as the following:
- Simple: Runs the linear regression expression y=Wx + b
- Estimator: Uses TensorFlow's built-in estimator to help automate training, testing, and predicting
- Polynomial: Uses TensorFlow (this time without an Estimator) to run training and predict a polynomial linear regression expression
We can find it on the GitHub repository at https://github.com/cleveranjos/SSE-LinearRegression and download it as a ZIP file to your computer using the green Clone or download button.
Unzip the package at any location on the computer...
