Machine Learning with Big Data and TensorFlow on Google Cloud Part II
Machine Learning with Big Data and TensorFlow on Google Cloud Part II


This training session will be conducted on Google Cloud Platform (GCP) and will use GCP to run TensorFlow. All you need is a laptop with a modern browser.
In the session, you will walk through the process of building a complete machine learning pipeline covering ingest, exploration, training, evaluation, deployment, and prediction:
Data pipelines and data processing: You will learn how to explore and split large data sets - for this part of the session you will be using SQL and Pandas on BigQuery and Cloud Datalab.
Model building: The machine learning models in TensorFlow will be developed on a small sample locally. The preprocessing operations will be implemented using Apache Beam, so that the same preprocessing can be applied in streaming mode as well. The preprocessing and training of the model will be carried out GCP.
Model Inference and Deployment: The trained model will be deployed as a REST microservice and predictions invoked from a web application.


Coming Soon

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