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Build, Train and Deploy ML Models with Keras on Google Cloud

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Google Cloud

Build, Train and Deploy ML Models with Keras on Google Cloud

This course is part of multiple programs.

49,478 already enrolled

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
4.4

(2,775 reviews)

Intermediate level
Some related experience required
Flexible schedule
Approx. 13 hours
Learn at your own pace
89%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.4

(2,775 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.

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)
Google Cloud Training
Google Cloud
1,696 Courses2,825,598 learners

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Google Cloud

Recommended if you're interested in Machine Learning

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4.4

2,775 reviews

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