
Unlocking Creativity with Azure OpenAI
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In this chapter, we significantly enhanced our movie recommender solution, adding layers of functionality that make it both more intelligent and user-friendly. We began by setting up the necessary keys and credentials, ensuring our program could securely interact with the required APIs and services. This setup is crucial because it allows our system to access powerful resources, such as OpenAI’s embedding models, which are key to understanding and processing the data.
Next, we integrated a Netflix dataset directly from Kaggle into our Jupyter notebook. By organizing this dataset into a pandas
DataFrame, we created a structured environment that facilitates efficient data manipulation and analysis. This step is vital because a clean, well-organized dataset is the foundation for any data-driven solution, enabling us to focus on extracting meaningful insights.
After loading the data, we zeroed in on the titles and descriptions of the shows, recognizing that these text...