Examining LLMs data generation and BigQuery DataFrames
Data processing and machine learning operations have been difficult to separate in big data analytics
This synthetic data can simulate operational or production data for ML model training or mathematical model evaluation
BigQuery DataFrames is an open-source Python package with pandas-like DataFrames and scikit-learn-like ML libraries for huge data
Vertex AI provides generative AI, including cutting-edge models, and Google Cloud Functions allows computational extensibility
Let’s use BigQuery DataFrames and LLMs to produce synthetic data in BigQuery
As with the given schema, run the LLM-generated code remote function on the indicator dataframe
BigQuery DataFrames integrates easily with your data warehouse, Vertex AI, and the advanced Gemini model
BigQuery DataFrames and LLMs may easily generate synthetic data, alleviating data privacy concerns and boosting AI development
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