Machine Learning on Google Cloud

Discover the fundamental concepts of machine learning on Google Cloud and the applications of the Vertex AI platform. Learn to build, train, and deploy AutoML machine learning models without writing any code. Gain insights into best practices for implementing machine learning on Google Cloud and understand responsible AI practices.

Learn essential techniques for improving data quality and performing exploratory data analysis. Build and train AutoML models using Vertex AI and BigQuery ML, optimize and evaluate models, and create repeatable and scalable training, evaluation, and test datasets.

Master the creation of TensorFlow and Keras machine learning models, including their key components. Explore the usage of the tf.data library, Keras Sequential and Functional APIs, and learn to deploy ML models at scale with Vertex AI.

Delve into the Vertex AI Feature Store and understand the key aspects of good features. Learn feature engineering using BigQuery ML, Keras, and TensorFlow, and explore data preprocessing and feature exploration using tf.Transform.

Understand data management, governance, and preprocessing options. Identify when to use Vertex AutoML, BigQuery ML, and custom training, and implement Vertex Vizier Hyperparameter Tuning. Gain knowledge of creating batch and online predictions, model monitoring, and pipelines using Vertex AI.