Book recommendation

Keywords: Book, recommendation

Background

People are using different types of books use to read so the author collected the dataset to know which books people are using to read according to the ratings that have been given by readers. The data set contains 271360 rows and 5 columns and another dataset contains 1149780, rows and 3 columns. There are very few null values present in the data set. So, the author did not drop those nan values instead dropping author fill those values with forward values. Here the prediction of most purchased books is the problem statement of the author so the author used an artificial neural network. And the author got a better prediction.

Aim & Objectives

Aim
To Predict the Book Recommendation Using DL Techniques
Objective
Design an ANN-based system for personalized book recommendations, enhancing user engagement and reading experiences.
Develop an ANN model that effectively captures user preferences to suggest relevant and diverse book choices.
Evaluate the ANN's recommendation accuracy and adaptability, ensuring seamless integration into online book platforms.

Research Methodology

ANN Technique used

Software & Tools

Jupyter, Google Collab

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