This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.
TensorFlow on Google Cloud
This course is part of multiple programs.
Instructor: Google Cloud Training
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(2,770 reviews)
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.
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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
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Recommended if you're interested in Machine Learning
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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.