Billion Dollar Movie Classifier

Inspiration

To apply probabilistic machine learning model in predicting movie earnings.

What it does

This model can predict whether a movie will be earning Billion dollar gross income or not with taking two features(rating,Budget) as input.

How I built it

I have used Naive Bays Probabilistic Algotrithm to build this classifier model. Total steps can be outlined as follows:

1.Importing Dataset( Billio_data and BillionLess data)and cleaning NAN value. 2.Importing Merge data after auditing 3.Splitting data into train and test as 80:20 also sorting data class wise for at some next step use. 4.Traing model(pred) with Naive Bays Binary Classifier having threshold as 0.5. 5.Calculating train error 6.Testing The model 7.Calculating Testing error 8.Getting the output with user data.

Challenges I ran into

1. To collect the data from API was a bit of challenge as there were some missing values. 2.During training the model there was an error "LinAlg error" as one of the matrix was singular i,e the detriment was zero and the algorithmic operation was not possible.I found two attributes have strong corelation and I solved this error by dropping one of them. ## Accomplishments that I am proud of This model has good accuracy and can predict a movie whether it will earn billion dollar or not in a very efficient way,which might be helpful in Movie business. ## What I learned I learnt to use API in AWS data exchange platform. I also learnt applying Naive Bays algorithm to classify a real business problem. ## What's next for Billion Dollar Movie Classifier I like to deploy this model in web and mobile platform at next stage.

Built With

• python