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Google Cloud

Serverless Machine Learning with Tensorflow on Google Cloud Platform

Google Cloud and Google via Coursera

This course may be unavailable.

Overview

This one-week accelerated on-demand course provides participants a a hands-on introduction to designing and building machine learning models on Google Cloud Platform. Through a combination of presentations, demos, and hand-on labs, participants will learn machine learning (ML) and TensorFlow concepts, and develop hands-on skills in developing, evaluating, and productionizing ML models.

OBJECTIVES

This course teaches participants the following skills:

● Identify use cases for machine learning

● Build an ML model using TensorFlow

● Build scalable, deployable ML models using Cloud ML

● Know the importance of preprocessing and combining features

● Incorporate advanced ML concepts into their models

● Productionize trained ML models


PREREQUISITES

To get the most of out of this course, participants should have:

● Completed Google Cloud Fundamentals- Big Data and Machine Learning course OR have equivalent experience

● Basic proficiency with common query language such as SQL

● Experience with data modeling, extract, transform, load activities

● Developing applications using a common programming language such Python

● Familiarity with Machine Learning and/or statistics

Google Account Notes:
• Google services are currently unavailable in China.

Syllabus

Welcome to Serverless Machine Learning on Google Cloud Platform

Module 1: Getting Started with Machine Learning

Module 2: Building ML models with Tensorflow

Module 3: Scaling ML models with Cloud ML Engine

Module 4: Feature Engineering

Taught by

Google Cloud Training

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