An Machine Learning algorithm to predict the Audiobook Buying Behavior of the customers
This is a Machine Learning Model that i created to predict the Audiobook Buying Behaviour of the Customers.
The dataset was collected over a period of 2.5 years, among which 2 years is used to accumulate the data and 6 months are used to calculate the targets.
The dataset is avilable in the Audiobooks_data.csv file.
The dataset consists of 4474 samples which we divide into:
- Training Data: 3579 samples
- Validation Data: 447 samples
- Test Data: 448 samples
The Audiobook_preprocessing.ipynb loads the data from the CSV file and preprocesses it (Balancing, Scaling, Standardization and Shuffling). After that, we save the Training Data, Validaton Data and the Test Data in Audiobooks_data_train.npz, Audiobooks_data_train.npz, Audiobooks_data_train.npz respectively as tensors. The Audiobook Machine_Learning model.ipynb is the model which we train using the data in the mentioned tensor files.
This particular model is 90% accurate (measured by the accuracy on the test data)