Music Recommendation Backend with Spring Boot and Neo4j

سرفصل های دوره

Learn how to build a Music Recommendation Backend with Spring Boot, Neo4j, Spring Cloud, and Collaborative Filtering

1. Introduction

1. Introduction

2. Project Setup

1. Create Microservices - Spring Cloud

3. Keycloak Server Setup

1.1 docker-compose.zip

1.2 notes.zip

1. Keycloak Integration Part 1

2.1 mysql-docker-compose.zip

2.2 postgres-docker-compose.zip

2. Keycloak Mysql Database Connection

4. Auth Service

1. Create User and Email Verification - Keycloak Integration

2. Implement Forgot Password - Keycloak Integration

5. User Service

1. User Profile Update And Image Upload with BunnyNet Integration

6. Music Service - Neo4J Integration

1. Create Models and Neo4j Repositories

2. Business Layer & Cipher Queries

3. REST API - (GenreApi, SongApi, AlbumApi, PlaylistApi)

4. Add user PLAYS songs Relationship & Get User Playlist Songs (Projection)

5. Get Artist Songs and Album Songs using Neo4JClient

6. Update User, Album and Playlist Details using Cipher Query SET

7. Update Song Details with Cipher Query SET

8. Update Posted Comment and Genre

9. Get Paginated Song Comments

10. AILarge Language Model - User Comment Analysis using LangChain and ChatGPT

11. Instant Release Song or Album

12. Add Spring Security

13. Release Scheduled Song or Album

14. BunnyNet Video Processing Webhook Status{FNISHED}

15. Artist Create Song - Complete BunnyNet Integration

7. Music Recommendation

1. Artist Followers Recommendation - Collaborative Filtering Cipher Query

2. Song Likes Similarity Recommendation Cipher Query Full Explanation

3. Artist Interest Recommendation - Sentiment Analysis through LLM

4. Song Play History Recommendation Cipher Query

5. Recommend latest songs for the Artists you Follows

6. Final Recommendation Cipher Query using UNION

7. Final Music Recommendation Java Implementation - Powerful Real-World Example

8. Messaging Service

1. Configure JavaMailSender And Thymeleaf Template Engine

2. Implement Send Send Song Comments and bind details to the template

3. Add Notification Business Logic and Create Auth Feign Client

4. Complete send email and intercept request token

9. Task-Scheduler Service

1. Task managent (CRUD)

2. Implement Task Scheduling

3. NFLOW integration and create publish workflow (State Machine)

4. Complete Publish Album or Songs

5. Feign Client Configuration with Client Credentials Grant Type

10. Extra

1. Send User Comment Email to an Artist

2. Sync music-service User with the user-service User

3.1 docker-compose.zip

3. Dockerizing microservices

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تولید کننده: Udemy