Exploring synthetic data generation with BigQuery DataFrames and LLMs
In the realm of big data analytics, a common challenge has been the separation between data processing and machine learning workflows. Traditionally, data engineers would use tools like Apache Spark for large-scale data processing in data warehouses like BigQuery, while data scientists would leverage libraries like pandas and scikit-learn for machine learning tasks. This disjointed …
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