django-ds-books

this repo presents a website where you can look for data science books and discuss data science topics. the website is built using Django3 Bootstrap4 with Postgresql database. i hosted a lite version of this project on heroku platform see it here

Machine Learning in this project

there is two applications of machine learning algorithms in this project:

1. Content Based Recommander System to similars to each book you can see the notebook where i build this recommander system using nlp(in this repo).
2. Super users can uppload new books so to ensure that they uppload only it books i built a book classifier that can classify books based on their descriptions on IT books or Not you can find more details about this classifier in this repo

Demo

• home page :

• category books page :

• book detail :

• discussions :

• category posts :

• topic posts :

• post detail :

• login form :

• register form :

• review form :

• search form :

Installation

1. clone the repo:

• if you have git installed: git clone https://github.com/YassineZITI/django-ds-books/edit/main/README.md
• if you don't. use this website to download the repo.

2. set up envirement:

• pip install virtualenv
• virtualenv venv
• pip install -r requirements.txt

3. Database:

• you need a postgres database for this project(we use an array field wich is available only in postgres django).
• replace the database configuration in settings.py file with yours.
• python manage.py makemigrations
• python manage.py migrate
• now you need some data(books) see next step.

4. populate database:

first method:

in this repo there are files called books.json and categories.json you will use those files to populate your database.

• py manage.py loaddata categories.json
• py manage.py loaddata books.json

second method:

if you didn't succeed with the 1st method you can use app_data.pkl and categories.pkl with the following steps instead.

• open your commande prompt and type py manage.py shell
• from blog.models import Book,Category
• import pickle
• with open('app_data.pkl','rb') as f:
• indentation books = pickle.load(f)
• with open('categories.pkl','rb') as f:
• indentation categories = pickle.load(f)
• for i in categories:
• indentation category = Category(name=i)
• indentation ` category.save()
• for i in books:
• indentation book=Book(ISBN=i['isbn13'],title=i['title'],description=i['description'],author=i['authors'],publisher=i['publisher'],published=i['year'],pages=i['pages'],stars=i['rating'],price=i['price'],image=i['image'],category=Category.objects.get(name=i['category']),similar_books=i['similar'],embedding=i['embedding'])
• indentation book.save()

5. start server: py manage.py runserver

Improvements

• add like option on posts and comments.
• add models for machine learning models.
• add profile section for users.
• add admin dashboard.
• ...

Contribution

Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given. Please star the repo and feel free to use it. ....