Book-Genre-Classification---Multi-Label-Text-Classification

this tutorial, I will show you how to predict Genres from the description of a books. We will build a multi-label model that’s capable of detecting different types of genre for each summary. We tune the hyper-parameters and plot graphs to find the best linear model.

Steps :

1. Read Data
2. Data Pre-Processing
3. Visualize the Data
4. Data Transformation
5. Training Classifier
6. Calculate Accuracy
7. Tune HyperParameters
8. Finalize the Best Model

Steps to Run the code provided:

1. Download the Dataset from http://www.cs.cmu.edu/~dbamman/booksummaries.html#:~:text=This%20dataset%20contains%20plot%20summaries,Creative%20Commons%20Attribution%2DShareAlike%20License
2. Unizip the Dataset
3. Download the ipynb file.
4. Put both ipynb file and dataset, "Summaries.txt" in the same folder
5. Run the python file