Key Features:

1. User Behavior Analysis:

   • Track and analyze user interactions with the platform, including page views, clicks, and time spent on content.

2. Personalized Recommendations:

   • Generate content recommendations tailored to each user's interests and preferences.

3. Machine Learning Integration:

   • Implement machine learning algorithms to improve recommendation accuracy over time.

4. Content Categorization:

   • Automatically categorize content into different topics and tags to enhance recommendation relevance.

5. A/B Testing:

   • Set up A/B testing capabilities to evaluate the effectiveness of different recommendation strategies.

6. Real-Time Updates:

   • Ensure recommendations are updated in real time based on the latest user interactions.

7. User Privacy and Data Security:

   • Adhere to privacy regulations and implement data security measures to protect user information.

8. Admin Dashboard:

   • Provide an admin dashboard to monitor recommendation performance and adjust algorithm parameters.

Required Skillsets:

1. Machine Learning:

   • Experience with machine learning frameworks like TensorFlow, PyTorch, or Scikit-Learn for developing recommendation algorithms.

2. Backend Development:

   • Proficiency in backend technologies such as Python (with Django or Flask) or Node.js.

3. Data Analysis:

   • Skills in data analysis and manipulation, particularly with SQL and NoSQL databases like MongoDB.

4. Frontend Development:

   • Knowledge of JavaScript, HTML5, and CSS3 for integrating recommendations into the platform's user interface.

5. API Development:

   • Experience in building and consuming RESTful APIs for data exchange between the recommendation engine and the platform.

6. Data Privacy and Security:

   • Understanding of data privacy laws (e.g., GDPR, CCPA) and best practices in data security.

7. DevOps Skills:

   • Familiarity with deploying machine learning models and maintaining them in a production environment.

8. Testing and Optimization:

   • Proficiency in testing and optimizing algorithms for performance and scalability.