A Machine Learning model is made through a normal work flow of a machine learning project.
Datasets were scraped from IMDb, taking variables related to movies.
Firstly a process of data preparation takes places to make sure the features to be used are well structured, missing data is filled and also some important variables.
Secondly a first iteration is made, it means, a simple model is tested with the dataset to know how exactly it makes predictions.
Once that the score of the first iteration is known, processes such as Feature engineering, Cross validation, Comparison of Learning curve and Validation curve and Model selection take place to improve the model.
At the end the selected mode is optimized by searching for the best parameters to make the best prediction.