Applying collaborative filtering on GoodReads' book reviews.
If you are looking to skim over the project without going into too much detail, you can always access it through here.
Big data is now being utilized at a level that we could have never previously imagined, but the important part still remains on how we apply the data in a business context, and how we make the most out of it. For online book retailers such as GoodReads, product ratings can play a huge role for making sound business decisions. As the data on product ratings continue to grow over time, companies can take advantage of this information and enhance Consumer experiences. I will be attempting to implement a recommendation system, for recommending product that Consumers are interested in purchasing.
The dataset I will be using is from www.kaggle.com.
I have also provided the direct link below if you wish to view the dataset I used to build my model:
https://www.kaggle.com/gnanesh/goodreads-book-reviews
This project was completed using Jupyter Notebook and Python with Pandas.
This dataset also requires heavy manipulation on our raw data before running the algorithm, and I will continue to perform other analysis in the future with my programming knowledge!