statmike/bigquery-data-science

Use when calling Gemini, TimesFM, TabFM, or pre-trained Cloud AI services from BigQuery SQL or BigFrames — generation (AI.GENERATE*, AI.COUNT_TOKENS), managed scoring/classification (AI.IF, AI.SCORE, AI.CLASSIFY, AI.AGG), embeddings and vector/hybrid search (AI.EMBED, VECTOR_SEARCH, AI.SEARCH), forecasting/prediction (AI.FORECAST, AI.PREDICT, AI.KEY_DRIVERS), and Cloud AI service models (ML.PROCESS_DOCUMENT, ML.TRANSLATE, ML.TRANSCRIBE).

Use FIRST when someone wants to predict, classify, forecast, embed, search, extract, or explain data in BigQuery and needs to choose between a trained model (bigquery-ml — CREATE MODEL + ML.*), a zero-training generative or foundation model function (bigquery-ai — AI.* + TimesFM + TabFM), or a pre-trained Google Cloud AI service model (ML.PROCESS_DOCUMENT, ML.TRANSLATE, ML.UNDERSTAND_TEXT, ML.ANNOTATE_IMAGE, ML.TRANSCRIBE).

Use when training, evaluating, deploying, or monitoring a machine learning model in BigQuery with SQL (CREATE MODEL and ML.* functions) — picking a model type, choosing a preprocessing function, point-in-time feature retrieval, causal inference (including AI.CAUSAL_EFFECT), or production retraining pipelines across 23 model types, 49 functions, 18 workflows, and 8 pipelines.