For my Practical AI class, I am working on a group project where we are leveraging machine learning to predict the outcomes of NFL games for the 2020 season. The project consists of two primary elements: the machine learning models, and the web application. Our models are created using data from a wide array of sources. In addition to NFL statistics, we are taking into account betting data to inform our model.
Each week, our web application updates with the schedule of games that are happening that week, as well as our predictions for those games. We provide links to previous weeks predictions so that users can see how our predictions have done in the past. The website updates weekly, and uses the model to generate the predictions that are displayed on the website.
We are using Google Cloud Console for hosting our web application(Google App Engine), as well as for our model creation(AutoML/Tables).
For my Practical AI class, I am working on a group project where we are leveraging machine learning to predict the outcomes of NFL games for the 2020 season. The project consists of two primary elements: the machine learning models, and the web application. Our models are created using data from a wide array of sources. In addition to NFL statistics, we are taking into account betting data to inform our model.
Each week, our web application updates with the schedule of games that are happening that week, as well as our predictions for those games. We provide links to previous weeks predictions so that users can see how our predictions have done in the past. The website updates weekly, and uses the model to generate the predictions that are displayed on the website.
We are using Google Cloud Console for hosting our web application(Google App Engine), as well as for our model creation(AutoML/Tables).