This course explores the GCP (Google Cloud Platform) machine learning (ML) tools, services, and capabilities, and different stages in the Google Cloud Platform machine learning workflow. This 14-video course demonstrates a high-level overview of different stages in Google Cloud Platform machine learning workflow. You will examine the features of BigQuery, and how to use Big Query ML to create and evaluate a binary logistic regression model using Big Query ML statement. Next, learners will observe how to use the Google AI Platform and Google Cloud AutoML components and features used for training, evaluating, and deploying ML models. You will learn to train models by using the built-in linear learner algorithm, submit jobs with GCloud and Console, create and evaluate binary logistic regression models, and set up and work with Cloud Datalab. You will learn to use AutoML Tables to work with data sets, to train machine learning models for predictions. Finally, you will work with Google Cloud AutoML Natural Language to create custom ML models for content category classification.