Event_Sangam

Event_Sangam

Its a Machine learning based a Django Full Stack Website for Event Management, which contains many features create, delete Event, Todo list etc and advanced feature that is Movie Recomendation system

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Event_Sangam

Event_Sangam

Its a Machine learning based a Django Full Stack Website for Event Management, which contains many features create, delete Event, Todo list etc and advanced feature that is Movie Recomendation system

The problem Event_Sangam solves

Create, edit, and organise notes, documents and web clippings.
Create and manage to-do lists and tasks.
User can able to login and singup into the website.
Their is a super user page is also there where user can able to
Allow users to use Kanban-style boards to manage tasks and projects.
Format texts with options such as headings, bullet points and links.
Easily rearrange and organize content with a user-friendly drag-and-drop interface.
Share documents and collaborate with others in real-time.
Save web articles, images, and content directly into the web app.
Create event calendars and set reminders.
Each tasks can have a deadline.
Ability to set different reminders before deadline (1 hour before, 1 day before etc).
Ability to add labels of different types and customizable colors associated with each of the labels.
Use pre-designed templates for tasks, projects, and more.
Edit and view content even without an internet connection.
Utilize more advanced text formatting options, including code blocks, inline databases, and equations.
View and restore previous versions of documents.
Customize access and permissions for — users and teams.
Ability to filter tasks by labels.
Ability to search across all tasks with advanced search options where you can also specify labels, deadline etc while searching.
And its advanced features is that user can predict the coice of movie for via entering a movie name via Machine Learning

Challenges I ran into

Challenge: Cleaning and preparing data for machine learning models can be time-consuming. Real-world data is often messy and may require extensive preprocessing.
Solution: Used Django management commands or custom scripts to automate data cleaning processes like Pandas and numpy is a powerful library for data manipulation and cleaning.
Challenge: Training and predicting with machine learning models can be time-consuming processes that might not fit well into the synchronous request-response cycle of web applications.
Solution: Used google collab instead of jupiter notebook for handling asynchronous tasks. This allows you to offload time-consuming tasks such as model training or predictions to background workers.
Clallenge: To create todo list for the the website.
Solution: I need to create an spterate Django app for it.
Challenge: Managing user authentication and authorization, ensuring that different roles (e.g., event organizers, attendees) have the appropriate permissions.
Solution: Utilize Django's built-in authentication system and implement role-based access control. Third-party packages like Django Allauth can enhance authentication features.

Discussion