When plunging into predictive analytics, we often forget to talk about the data preparation necessary for it. In this latest Data Science Central webinar, we will use a movie database as a fun example, and we’ll work towards creating a model to predict a movie’s overall rating—to see if certain actors, the genre, or even movie length has an impact on its rating.
We will also discuss what to keep in mind in terms of data preparation as we work towards developing a training dataset; making sure that the data preparation is repeatable, that all team members understand the process (to ensure buy-in), and that additional information can be created from the data available. You’ll learn how Rapid Insight’s Veera platform makes all of this easy, saving time and resources.
Key highlights include:
Democratizing the data, or creating a process that most people would be able to follow, regardless of professional background or industry
Ensuring buy-in because it helps you communicate to everyone in the organization about the model and data preparation
Creating a repeatable and schedulable workflow for data preparation
Predicting movie ratings and looking at what type of reviews a movie pitch might get
Jon MacMillan, Senior Data Analyst – Rapid Insight
Alex Herbert, Sales Manager – Rapid Insight
Stephanie Glen, Editorial Director – Data Science Central