Inspiration
I was inspired to create a movie recommendation system that could leverage the power of MySQL HeatWave for efficient data analysis and Oracle APEX for building a user-friendly interface. The objective was to provide users with personalized recommendations based on their preferences and historical data from the MovieLens dataset.
What it does
Throughout this project, I gained a deeper understanding of database management systems, particularly MySQL HeatWave, and how it can be utilized for OLAP (Online Analytical Processing) and AutoML (Automated Machine Learning) tasks. I also familiarized myself with Oracle APEX and its capabilities for rapidly developing web applications with minimal coding.
How we built it
Setting up MySQL HeatWave Cluster: I configured a HeatWave cluster to handle OLAP queries efficiently, ensuring quick analysis of large datasets. Creating Bastion Server: A secure Bastion server was established to manage access to the MySQL data and ensure data security. Downloading and Transforming MovieLens Dataset: I retrieved the MovieLens dataset files and transformed them into a format suitable for MySQL HeatWave, ensuring data consistency and integrity. Adding MovieLens Data to MySQL HeatWave: The transformed data was loaded into MySQL HeatWave tables, allowing for fast querying and analysis. Creating and Testing HeatWave AutoML Recommender System: I implemented an AutoML-based recommendation system within HeatWave to generate personalized movie recommendations for users. Creating Base Movies Database Tables: I designed the base database tables for the Movie App, ensuring efficient storage and retrieval of movie information. Querying Information: I executed queries on the movies and predictions tables to retrieve relevant information for generating recommendations. Creating Low Code Application with Oracle APEX: Leveraging Oracle APEX, I developed a user-friendly application interface for users to interact with the recommendation system. Setting up APEX Application and Workspace: The APEX application and workspace were configured to host the movie recommendation app and manage user access. Exploring Movie Recommendation App: Finally, I thoroughly tested the movie recommendation app, ensuring that users could easily access and explore personalized movie recommendations.
Challenges we ran into
I felt like in some labs the instructions weren't clear which took quite a while for me to figure out the issue I have facing. Also, In lab 5 they haven't provided any instructions to add ingress rule which is required to connect to mysql heat wave database. Fortunately I was able to figure out from spending a good amount of my time. So Lab-5 instructions should be added to make the workshop easy to fellow for someone who is new to this field.
What we learned
How to use OCI and tools such as MySQL HeatWave, APEX, Oracle Rest Services and many more.
What's next for Movie Recommendation
Would like to use these tools for building different recommendation system in food and music industry.
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