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
本课程是多个项目的一部分。
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您将学到什么
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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作业
4 项作业
授课语言：英语（English）
了解顶级公司的员工如何掌握热门技能
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该课程共有6个模块
This module provides an overview of the course and its objectives.
涵盖的内容
1个视频
This module introduces the TensorFlow framework and previews its main components as well as the overall API hierarchy.
涵盖的内容
4个视频1篇阅读材料1个作业
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.
涵盖的内容
10个视频1篇阅读材料1个作业2个应用程序项目
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.
涵盖的内容
10个视频1篇阅读材料1个作业2个应用程序项目
In this module, we describe how to train TensorFlow models at scale using Vertex AI.
涵盖的内容
3个视频1篇阅读材料1个作业1个应用程序项目
This module is a summary of the Build, Train, and Deploy ML Models with Keras on Google Cloud course.
涵盖的内容
4篇阅读材料
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授课教师评分
4.5 (196个评价)
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人们为什么选择 Coursera 来帮助自己实现职业发展
Felipe M.
自 2018开始学习的学生
''能够按照自己的速度和节奏学习课程是一次很棒的经历。只要符合自己的时间表和心情，我就可以学习。'
Jennifer J.
自 2020开始学习的学生
''我直接将从课程中学到的概念和技能应用到一个令人兴奋的新工作项目中。'
Larry W.
自 2021开始学习的学生
''如果我的大学不提供我需要的主题课程，Coursera 便是最好的去处之一。'
Chaitanya A.
''学习不仅仅是在工作中做的更好：它远不止于此。Coursera 让我无限制地学习。'
学生评论
4.4
2,803 条评论
- 5 stars
62.04%
- 4 stars
24.72%
- 3 stars
8.84%
- 2 stars
2.67%
- 1 star
1.71%
显示 3/2803 个
PS
5
已于 Aug 5, 2019审阅
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 .
YG
4
已于 Apr 4, 2019审阅
The procedure to connect to the cloud datalab was time consuming to do it every time.Suggestion : More topics in Core Tensorflow could be added. I enjoyed the course!
JZ
5
已于 Nov 3, 2022审阅
Quite a technical course with sophisticated lab sessions, but I got good hands-on experience on building NN models using Keras and TF functional API as well as deploying the model in Vertex AI.
常见问题
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.
更多问题
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