Machine Learning on Google Cloud Platform


LP Box Courses 2 Video Courses
LP Box quiz No quiz sessions
LP Box Lab No hands-on labs
Duration 2h 2m

Learning Path Description

This learning path will introduce you to neural networks, TensorFlow, and Google Cloud Machine Learning Engine. Even if you don't have any previous experience with machine learning, that's okay, because these courses cover the basic concepts.

The first course explains the fundamentals of neural networks and how to implement them using TensorFlow. Then it shows you how to train and deploy a model using Cloud ML Engine.

The second course explains how to build convolutional neural networks, which are very effective at performing object detection in images, among other tasks. It also shows how to visualize a model's performance using TensorBoard, reduce overfitting, and train a model on a custom cluster using Cloud ML Engine.

Both of these courses include hands-on demos you can do yourself. Then you can test what you’ve learned by taking the exam.

Learning Objectives

  • Describe how an artificial neural network functions
  • Run a simple TensorFlow program
  • Train a model using a distributed cluster on Cloud ML Engine
  • Increase prediction accuracy using feature engineering and both wide and deep networks
  • Deploy a trained model on Cloud ML Engine to make predictions with new data
  • Build a Convolutional Neural Network in TensorFlow
  • Analyze a model’s training performance using TensorBoard
  • Identify cases of overfitting and apply techniques to prevent it
  • Scale a Cloud ML Engine job using a custom configuration

Intended Audience

  • Data professionals


This Learning Path Includes

  • 2 video courses
  • 1 exam


If you have thoughts or suggestions for this learning path, please contact Cloud Academy at

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Machine learning is a hot topic these days and Google has been one of the biggest newsmakers. Recently, Google’s AlphaGo program beat the world’s No. 1 ranked Go player. That’s impressive, but Google’s machine learning is being used behind the scenes every day by millions of people. When you search for an image on the web or use Google Translate on foreign language text or use voice dictation on ...


Course Description Once you know how to build and train neural networks using TensorFlow and Google Cloud Machine Learning Engine, what’s next? Before long, you’ll discover that prebuilt estimators and default configurations will only get you so far. To optimize your models, you may need to create your own estimators, try different techniques to reduce overfitting, and use custom clusters to ...


OverviewThis exam will test the concepts, services and methods discussed in the Google Cloud Machine Learning Engine learning path. You have 20 minutes to complete 20 multiple-choice questions. You must score 60 percent or higher to pass this exam.Questions will focus on the following topics:Neural networksTensorFlowGoogle Cloud Machine Learning EngineOnce you begin your exam session:You can ...
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Machine Learning on Google Cloud Platform
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