Memberikan penjelasan untuk model, untuk mengklarifikasi bagaimana fitur tertentu memengaruhi prediksi yang diberikan dan juga model secara keseluruhan.
Mempelajari lebih lanjut komponen yang membentuk model dengan menggunakan bobot model.
Karena Anda dapat menggunakan berbagai jenis model di BigQuery ML, fungsi yang tersedia untuk setiap model bervariasi. Lihat Perjalanan pengguna menyeluruh untuk setiap model guna mengetahui fungsi spesifik yang tersedia untuk setiap model.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-09-04 UTC."],[[["\u003cp\u003eBigQuery ML enables the creation and operationalization of machine learning models using SQL over BigQuery data.\u003c/p\u003e\n"],["\u003cp\u003eModel development in BigQuery ML involves creating, preprocessing, tuning, evaluating, inferencing, and explaining models.\u003c/p\u003e\n"],["\u003cp\u003eBigQuery ML supports both automatic and manual feature preprocessing via functions and the \u003ccode\u003eTRANSFORM\u003c/code\u003e clause.\u003c/p\u003e\n"],["\u003cp\u003eHyperparameter tuning is used to refine the model to better fit the training data.\u003c/p\u003e\n"],["\u003cp\u003eThe available functions vary between each type of model, detailed in the end-to-end user journey for each model.\u003c/p\u003e\n"]]],[],null,["# Model creation\n==============\n\nBigQuery ML lets you build and operationalize machine learning (ML)\nmodels over data in BigQuery by using SQL.\n\nA typical model development workflow in BigQuery ML looks similar\nto the following:\n\n1. Create the model using the [`CREATE MODEL` statement](/bigquery/docs/reference/standard-sql/bigqueryml-syntax-create).\n2. Perform feature preprocessing. Some preprocessing happens [automatically](/bigquery/docs/reference/standard-sql/bigqueryml-auto-preprocessing), plus you can use [manual preprocessing functions](/bigquery/docs/reference/standard-sql/bigqueryml-preprocessing-functions) inside the [`TRANSFORM` clause](/bigquery/docs/reference/standard-sql/bigqueryml-syntax-create#transform) to do additional preprocessing.\n3. Refine the model by performing [hyperparameter tuning](/bigquery/docs/hp-tuning-overview) to fit the model to the training data.\n4. [Evaluate the model](/bigquery/docs/evaluate-overview) to assess how it might perform on data outside of the training set, and also to compare it to other models if appropriate.\n5. [Perform inference](/bigquery/docs/inference-overview) to analyze data by using the model.\n6. Provide [explainability](/bigquery/docs/xai-overview) for the model, to clarify how particular features influenced a given prediction and also the model overall.\n7. Learn more about the components that comprize the model by using [model weights](/bigquery/docs/weights-overview).\n\nBecause you can use many different kinds of models in BigQuery ML,\nthe functions available for each model vary. See the\n[End-to-end user journey for each model](/bigquery/docs/e2e-journey) to see\nthe specific functions available for each model."]]
