Book Recommendation Project
Welcome to our first club-wide project! We have partnered with GLHS Media Center to apply machine learning to help students discover new books.
Based on students’ interests and past books they have read, we will create/train a recommendation engine that can recommend new books to read, similarly to how YouTube recommends new videos to watch and Netflix recommends new movies to watch.
Important information for club members who want to contribute:
BEFORE YOU START:
- Form a group. You may work individually if you wish.
- Fill out this form once you have decided who you are working with.
DATA:
- The GLHS media center has provided a dataset containing a list of all books available in the media center. This data can be accessed through Google Classroom.
- As a part of your project, you will need to find a dataset on readers' interests. You can use any publicly available dataset you want. For example, you could use Amazon Review Data, which contains over 50 million reviews from May 1996 – Oct 2018. You could also use this dataset on Kaggle, which is smaller and is easier to process.
STEPS TO CONTRIBUTE:
- Fork this GitHub repository.
- Save all your code in the forked repository.
- Update the README.md file to include your group member names and a general overview of your process.
- Once you are done with your project, submit a pull request on GitHub. See this link for more information.
CONTRIBUTORS