Book Buddy is a book recommendation system, built as the solution to the Algorithms track of the Microsoft Engage Challenge 2022.
Demo video link: Book Buddy Demo
Hosted web application: https://kavya-bhat-bookbuddy.herokuapp.com/
- Simple and actionable UI.
- Ability to search for books using only partial titles (in case you've forgotten the entire title).
- Search for other popular books, similar to the title searched for.
- Select an algorithm (options - brute force, KD Tree or Ball Tree) from the dropdown menu, and observe the processing time at the bottom of the results page.
- Ability to search for books by genre, such as Fiction or Philosophy.
Python : Python is a high-level, interpreted, general-purpose programming language, and the language of choice for building ML models.
PHP : A scripting language that helps make dynamic, interactive web pages.
Bootstrap : Open source CSS framework that helps design web pages easily and quickly.
Kaggle : An online community of data scientists - this is where I obtained the dataset for book details.
- Had little to no knowledge of ML before the Microsoft Engage Program's qualification announcement. It took over a week to understand the fundamentals, and grasp an idea for integration with a web application.
- Obtained working knowledge of PHP over the course of a few days, and began to code alongside the learning process.
- Started out with MySQL and PHP, and switched over to PostgreSQL in the last week as I needed to use Heroku Postgres for deployment. This required quite a few changes to the codebase.
- Deployed a full stack app with frontend, backend and database for the first time. Documentations and tutorials came to the rescue.
Feel free to open an issue on GitHub if you find bugs.
Feel free to open an issue on GitHub to add any additional features you feel could enhance this project.