[Note: those who RSVP'd 'Yes' will receive an Eventbrite link for registration. ] In this hands-on bootcamp, you will walk through the process of building a complete machine learning pipeline covering ingest, exploration, training, evaluation, deployment, and prediction. Along the way, we will discuss how to explore and split large data sets correctly using BigQuery and Cloud Datalab. The machine
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[Note: those who RSVP'd 'Yes' will receive an Eventbrite link for registration. ]
In this hands-on bootcamp, you will walk through the process of building a complete machine learning pipeline covering ingest, exploration, training, evaluation, deployment, and prediction. Along the way, we will discuss how to explore and split large data sets correctly using BigQuery and Cloud Datalab. The machine learning model in TensorFlow will be developed on a small sample locally. The preprocessing operations will be implemented in Cloud Dataflow, so that the same preprocessing can be applied in streaming mode as well. The training of the model will then be distributed and scaled out on Cloud ML Engine. The trained model will be deployed as a microservice and predictions invoked from a web application.
What you need:
Come with a laptop with an up-to-date web browser. We will supply a temporary GCP project that you can use to do the bootcamp.
Prerequisites:
Basic SQL, familiarity with Python and TensorFlow or equivalent knowledge as in this course on Coursera: Serverless Machine Learning with TensorFlow on GCP - https://www.coursera.org/learn/serverless-machine-learning-gcp. This is a full-day, advanced hands-on workshop (70% labs, 30% lecture), not a intro beginner session. If you don't meet the pre-requisite, you may find it difficult to do the labs in the workshop.
PARKING & TRANSPORTATIONS
This will be held in building B (room KIR-6THB-1-Backstreet/Banana Seat) at Google Kirkland. When you arrive you can park in a guest parking spot by building A, B or building D (P1 or P2).
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