Is your feature request related to a problem? Please describe.
Yes, the platform currently lacks tutorial recommendations and tutorial displays on user profile pages. This limits user engagement and makes it challenging for users to discover relevant content based on their preferences such as "New", "Featured" and "Top" tutorials. Additionally, tutorials are not displayed on user profile pages, which reduces the visibility of the content users have created or engaged with.

Describe the solution you'd like

• Implement algorithms to generate tutorial recommendations based on user preferences, such as latest tutorials, most liked tutorials, and popular tags.
• Integrate the recommender system into the platform's feed functionality, ensuring that users receive relevant tutorial suggestions when the corresponding criteria is selected.
• Display tutorials on user profile pages.
• Implement the section on the tutorial page which is hardcoded temporarily to recommend related tutorials to the user, enhancing content discoverability.

Describe alternatives you've considered
Considered using machine learning algorithms and TensorFlow.js to develop an advanced recommender system. However, this approach was dropped due to the following reasons:

• Time-Consuming: The implementation and integration process would be complex and time-intensive.
• Lack of Training Data: The current platform does not have sufficient training data to effectively train the machine learning models, which would limit the accuracy and effectiveness of the recommendations.

Additional context
Implementing a recommender system and displaying tutorials on profile pages will significantly enhance user experience by providing filtered content and increasing the visibility of tutorials. This will likely lead to higher user engagement, satisfaction, and retention. As the platform grows, these features will be crucial for maintaining a dynamic and user-focused environment.