This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.
Build, Train and Deploy ML Models with Keras on Google Cloud
Build, Train and Deploy ML Models with Keras on Google Cloud
This course is part of multiple programs.
Instructor: Google Cloud Training
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4.4
(2,777 reviews)
Intermediate level
Some related experience required
Flexible schedule
Approx. 13 hours
Learn at your own pace
89%
Most learners liked this course
What you'll learn
Design and build a TensorFlow input data pipeline.
Use the tf.data library to manipulate data in large datasets.
Use the Keras Sequential and Functional APIs for simple and advanced model creation.
Train, deploy, and productionalize ML models at scale with Vertex AI.
Skills you'll gain
Details to know
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Assessments
4 assignments
Taught in English
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There are 6 modules in this course
This module provides an overview of the course and its objectives.
What's included
1 video
This module introduces the TensorFlow framework and previews its main components as well as the overall API hierarchy.
What's included
4 videos1 reading1 assignment
Data is the a crucial component of a machine learning model. Collecting the right data is not enough. You also need to make sure you put the right processes in place to clean, analyze and transform the data, as needed, so that the model can take the most signal of it as possible. In this module we discuss training on large datasets with tf.data, working with in-memory files, and how to get the data ready for training. Then we discuss embeddings, and end with an overview of scaling data with tf.keras preprocessing layers.
What's included
10 videos1 reading1 assignment2 app items
In this module, we discuss activation functions and how they are needed to allow deep neural networks to capture nonlinearities of the data. We then provide an overview of Deep Neural Networks using the Keras Sequential and Functional APIs. Next we describe model subclassing, which offers greater flexibility in model building. The module ends with a lesson on regularization.
What's included
10 videos1 reading1 assignment2 app items
In this module, we describe how to train TensorFlow models at scale using Vertex AI.
What's included
3 videos1 reading1 assignment1 app item
This module is a summary of the Build, Train, and Deploy ML Models with Keras on Google Cloud course.
What's included
4 readings
Instructor
Instructor ratings
4.5 (189 ratings)Offered by
Recommended if you're interested in Machine Learning
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4.4
2,777 reviews
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Showing 3 of 2777
PS
5
Reviewed on Aug 5, 2019
Course is Best so far i learnt in Tensor Flow . It has all modules and content to be successful in Deep Learning and GCP Machine learning .
VC
5
Reviewed on May 17, 2020
I feel this course very valuable because it taught how to create an automated service in cloud with very huge data and working with distributed systems in production environment with minimal time.
TB
4
Reviewed on Oct 6, 2018
Great course as an introduction to TF, however, the labs are not as in depth as I'd have liked. Nonetheless, the course is well executed by the presenters.
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.