Develop and train custom TensorFlow models using Vertex AI, directly accessing data from BigQuery, to leverage a wide range of ML algorithms and neural network architectures.

Employ Vertex AI Workbench user-managed notebooks to write and execute scikit-learn code for various ML algorithms, enabling detailed performance analysis and customization.

Utilize BigQuery ML to execute several regression models within BigQuery, facilitating rapid experimentation and performance analysis using SQL queries.

Process the data in BigQuery with Dataproc and implement various machine learning models using SparkML for distributed computing capabilities.

Combine the use of BigQuery ML for initial rapid experimentation with Vertex AI for more complex model training and deployment, ensuring a comprehensive approach to model development and evaluation.