Image Understanding with TensorFlow on GCP

This 5-course specialization focuses on advanced machine learning topics using Google Cloud Platform where you will get hands-on experience optimizing, deploying, and scaling production ML models of various types in hands-on labs. This specialization picks up where "Machine Learning on GCP" left off and teaches you how to build scalable, accurate, and production-ready models for structured data, image data, time-series, and natural language text. It ends with a course on building recommendation systems. Topics introduced in earlier courses are referenced in later courses, so it is recommended

( 124 Reviews )

Created by: Google Cloud Training

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Overall Score : 88 / 100

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Course Description

This is the third course of the Advanced Machine Learning on GCP specialization. In this course,We will take a look at different strategies for building an image classifier using convolutional neural networks. We'll improve the model's accuracy with augmentation, feature extraction, and fine-tuning hyperparameters while trying to avoid overfitting our data. We will also look at practical issues that arise, for example, when you don't have enough data and how to incorporate the latest research findings into our models.You will get hands-on practice building and optimizing your own image classification models on a variety of public datasets in the labs we'll work on together. Prerequisites: Basic SQL, familiarity with Python and TensorFlowCOMPLETION CHALLENGEComplete any GCP specialization from November 5 - November 30, 2019 for an opportunity to receive a GCP t-shirt (while supplies last). Check Discussion Forums for details.

Time: 11h

Instructor Details

Google Cloud Training

4.4 Rating
124 Reviews

The Google Cloud Training team is responsible for developing, delivering and evaluating training that enables our enterprise customers and partners to use our products and solution offerings in an effective and impactful way. Google Cloud helps millions of organizations empower their employees, serve their customers, and build what's next for their businesses with innovative technology created in-and for-the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.

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4.4

124 total reviews

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By vincent p on 16-Feb-19

Several quicklabs issuesTPU quicklabs does not work. Always getting access error. I added manually the rights, but then I have an error about import apache-beam. AutoML Vision quicklabs needs to mention to enable per object ACL or you cannot set the ACL.Datalab is very very slow to start, very painful.

By Konstantinos S on 29-Mar-19

Most labs don't work or are pointless

By Jakub B on 26-Jun-19

Subscribing to this course only gives you option to run assignments on Qwik labs, and they're very poor for these kinds of assignments. You won't get any feedback on assignments anyway since there is no grader.If you want to check out the material it's better to just clone training-data-analyst from github and do these assignments on GCP free tier.

By Mark D on 21-Jan-19

Was worried this would be just another CNN course but it was so much more. Showing out to use existing models etc. The details on CNN is a little lite but that can be found elsewhere. What was really good was the batch normalization and using pre-trained models but just changing the dense layers to provide classification,

By bhadresh s on 23-Jan-19