Hello World !!! 😃

"The more that you read, the more things you will know. The more that you learn, the more places you'll go"

• Dr. Seuss

Code Overview of our Project:

project.mp4

Welcome to our book recommendation system!

Are you tired of scrolling through endless lists of books, trying to find the perfect one to curl up with? Look no further! Our recommendation system uses state-of-the-art algorithms to suggest books tailored specifically to your tastes. But that's not all - our system is also powered by machine learning, which means it's constantly learning and adapting to your reading preferences. The more you use it, the better it gets at finding books you'll love. Don't worry your info is safe with us.

With our system, you can enter in your favorite books and authors, and we'll generate personalized recommendations just for you. No more endless scrolling through Amazon trying to find something new to read. Let us do the work for you!.Just give us a few of your favorite titles and authors, and we'll conjure up a list of recommendations that will have you casting your own spells of literary enjoyment. Whether you're in the mood for a heart-wrenching romance or a mind-blowing fantasy or reality-bending fiction or just want to have a laugh, we've got you covered.

So why wait? Step into our magical world of reading today and discover your next literary adventure! Go ahead, give it a try. Who knows what magical stories you'll discover next? Happy reading!

Check our website at :

https://arjundotadex.github.io/Book-recommendation-system.github.io/

Why a Book Recommendation System ?

1. A book recommendation system can help users discover new and relevant books based on their reading history and preferences.
2. It can provide personalized recommendations to each user, which can make the process of finding a new book to read more efficient and enjoyable.
3. It can help users save time by filtering out books that they are not interested in, and instead presenting them with a curated list of options.
4. It can improve the user's reading experience by providing recommendations for books that are closely related to ones they have already enjoyed.
5. A book recommendation system can also be used to make recommendations to groups of users with similar reading interests, such as a book club or a community of readers with similar tastes.

Instructions:

This Website is Made with the use of only html, css, js and python so any beginner person can contribute in this project.You can check live webite here and suggest changes accordingly.If you want to do Non-Code contribution you can put up a public message in the repository.

This repo will be partcipating in the SheBuilds Hackathon 2022.

SheBuilds	Our Logo

😎😎All Noobs and pro PR's Are Welcome 😎😎

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This is a beginner-friendly repo, where you can be as much creative as you can with HTML, CSS, JS and Python

Rules for the Contribution.

1. Issues will be assigned on First Come First Service Basis.
2. You can create a new issue.
3. Maintainer will add a suitable lable, if the issue created by you is relevant.
4. Don't Spam the PR otherwise spam label can be added to your PR.
5. After creating a PR link the issue also.

Contributing

We welcome contributions of all kinds to the Book Recommendation System website! Whether you have a suggestion for a new feature, have found a bug that needs to be fixed, or want to contribute to the website's design or documentation, we appreciate your help. Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

Here are some guidelines to follow when contributing:

1. Before making a contribution, please check the project's open issues to see if someone else is already working on something similar. If you have a new suggestion or have found a bug, please open a new issue to let us know.
2. If you want to work on an existing issue or have a new idea for a feature, please comment on the issue to let us know that you are working on it. This will help to prevent duplication of effort.
3. All contributions should be made via pull request. When submitting a pull request, please make sure to include a clear description of the changes you have made and why they are necessary.
4. All code contributions should be accompanied by tests to ensure that the changes do not break existing functionality.
5. If you are making a non-code contribution (e.g. writing documentation, creating graphics), please make sure to follow the project's style guidelines and include any necessary attribution.

Final Guide:

1. Fork this repository.
2. Clone your forked copy of the project
3. Navigate to the project directory
4. Create a new branch(git checkout -b YourBranchName)
5. Make changes in source code.
6. Stage your changes(git add .) & commit your changes( git commit -m "<your_commit_message>")
7. Push your local commits to the remote repo( git push origin YourBranchName)
8. Create a PR

Thank you for your interest in contributing to the Book Recommendation System website! We appreciate your help and look forward to working with you.

Project Demo Video :

website.mp4

Our Team :

Arjun

Hey Folks my name is Arjun. I am a tech-enthusiastic person, a self-learner with a passion for innovation, and am learning the importance of applying classical strategies to modern-day projects.

Harsh Bajaj

Hey Folks my name is Harsh Bajaj. I am an Android Developer, a fire-fighter with a passion for creating and bulding new things. Currently I am learning Data Structures and Algorithms

Atharva Salitri

Hey Folks my name is Atharva Salitri, a high schooler interested in the world of software development. I like to learn new things and implement them to solve problems. I am a content writer and an avid reader

Arjumand Rashid

Hey Folks my name is Arjumand Rashid. I am a Machine Learning Enthusiast. Interested in encouraging other girls to code.I have a passion for understanding and working with data, and have experience with programming languages like Python etc.

Contributors :

About :

Our book recommendation system is a project that was created as part of the SheBuilds hackathon. SheBuilds is a 48-hour gender-focused hackathon with endless creativity. Students are challenged to further what they know by creating projects following their passions. Spending time on projects outside the classroom is the best way to not only learn what you love but also find new interests.

Our team of four highly enthusiastic individuals was inspired by the mission of SheBuilds and decided to focus on creating a tool that could help people discover new and engaging books to read. By leveraging machine learning techniques and a comprehensive dataset of books and user ratings, our book recommendation system is able to provide personalised recommendations to help users find their next great read. We are proud to have been a part of the SheBuilds hackathon and are excited to continue developing and improving our book recommendation system in the future.

Thank You!