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Data Science with Notebooks

Objectives Prepare a raw dataset of real estate listings for analysis through feature engineering. Enrich listings by using BigQuery's AI functions to analyze house photos for key visual features. Build and evaluate a K-means model with BigQuery Machine Learning (BQML) to segment properties into distinct clusters. Automate model creation by using the Data Science Agent to generate a clustering model with Python. Generate embeddings for house images to power a visual search tool, finding similar homes with text or image queries. Code: https://github.com/starttraining/Data... Chapter 00:40 Task 1. Open Lab Notebook in BigQuery 02:03 Task 2. Connect to a Runtime and Run Setup Code 04:38 Task 3. Data Preparation and Feature Engineering 08:35 Task 4. Multimodal Enrichment with AI Functions 12:24 Task 5. Model Training with K-Means Clustering 15:18 Task 6. Model Evaluation and Prediction 17:34 Task 7. Visualize and Interpret Clusters 24:47 Task 8. Generate Cluster Descriptions with Gemini Models 25:58 Task 9. Automate Modeling with the Data Science Agent 30:15 Task 10. Multimodal Search with Embeddings and Vector Search