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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you will use TensorFlow's distribution strategies and the Vertex AI platform to train and deploy a custom TensorFlow image classification model to classify an image classification dataset.
Register for this course and see more details by visiting:
OpenCourser.com/course/4nk3ug/running
What's inside
Syllabus
Running Distributed TensorFlow using Vertex AI
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Specializes in helping learners develop skills and knowledge in training machine learning models and deploying them on the Vertex AI platform
Offers an up-to-date exploration of training and deploying custom image classification models with TensorFlow's distribution strategies
Provides a self-paced, hands-on learning experience through the Google Cloud console
Led by Google Cloud Training, known for its expertise in training and deploying machine learning models
The course is appropriate for learners with some prior knowledge in machine learning, TensorFlow, and cloud computing
Save this course
Save Running Distributed TensorFlow using Vertex AI to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Running Distributed TensorFlow using Vertex AI with these
activities:
Python Refresher
Show steps
Strengthen the foundation in Python, ensuring readiness for the course.
Browse courses on
Python
Show steps
-
Review basic Python syntax and data structures.
-
Practice writing simple Python scripts.
TensorFlow Tutorial Practice
Show steps
Develop familiarity and comfort with TensorFlow by completing practice tutorials.
Browse courses on
TensorFlow
Show steps
-
Complete a TensorFlow tutorial on image classification.
-
Modify the tutorial code and experiment with different parameters.
-
Troubleshoot any errors encountered during the tutorial.
Interactive Codebook
Show steps
Solidify understanding of code functionality by creating an interactive codebook.
Browse courses on
Python
Show steps
-
Create a new notebook or document.
-
Import the TensorFlow library and any other necessary libraries.
-
Define functions and classes related to the image classification model.
-
Write detailed comments and explanations for each block of code.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Vertex AI Guided Tutorials
Show steps
Gain deeper insights into the Vertex AI platform through guided tutorials.
Browse courses on
Vertex AI
Show steps
-
Explore the Vertex AI documentation and tutorials.
-
Follow a guided tutorial on deploying a TensorFlow model to Vertex AI.
-
Experiment with different Vertex AI features and services.
Peer Code Review
Show steps
Enhance code quality and understanding through peer collaboration.
Browse courses on
TensorFlow
Show steps
-
Find a peer to collaborate with.
-
Share your code with your peer and ask for feedback.
-
Review your peer's code and provide constructive criticism.
Vertex AI Hands-on Workshop
Show steps
Enhance practical skills and gain hands-on experience with Vertex AI.
Browse courses on
TensorFlow
Show steps
-
Attend a hands-on workshop focused on Vertex AI.
-
Build and deploy a machine learning model using Vertex AI services.
Image Classification Model Report
Show steps
Demonstrate understanding of model development and evaluation by creating a comprehensive report.
Browse courses on
TensorFlow
Show steps
-
Train and evaluate the image classification model.
-
Analyze the model's performance and identify areas for improvement.
-
Write a detailed report summarizing the model development process, results, and insights.
Kaggle Image Classification Competition
Show steps
Challenge and test the limits of understanding through a competitive environment.
Browse courses on
TensorFlow
Show steps
-
Explore Kaggle competitions related to image classification.
-
Select a competition and build a submission using TensorFlow.
Python Refresher
Show steps
Strengthen the foundation in Python, ensuring readiness for the course.
Browse courses on
Python
Show steps
Show steps
Show steps
- Review basic Python syntax and data structures.
- Practice writing simple Python scripts.
TensorFlow Tutorial Practice
Show steps
Develop familiarity and comfort with TensorFlow by completing practice tutorials.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- Complete a TensorFlow tutorial on image classification.
- Modify the tutorial code and experiment with different parameters.
- Troubleshoot any errors encountered during the tutorial.
Interactive Codebook
Show steps
Solidify understanding of code functionality by creating an interactive codebook.
Browse courses on
Python
Show steps
Show steps
Show steps
- Create a new notebook or document.
- Import the TensorFlow library and any other necessary libraries.
- Define functions and classes related to the image classification model.
- Write detailed comments and explanations for each block of code.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Vertex AI Guided Tutorials
Show steps
Gain deeper insights into the Vertex AI platform through guided tutorials.
Browse courses on
Vertex AI
Show steps
Show steps
Show steps
- Explore the Vertex AI documentation and tutorials.
- Follow a guided tutorial on deploying a TensorFlow model to Vertex AI.
- Experiment with different Vertex AI features and services.
Peer Code Review
Show steps
Enhance code quality and understanding through peer collaboration.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- Find a peer to collaborate with.
- Share your code with your peer and ask for feedback.
- Review your peer's code and provide constructive criticism.
Vertex AI Hands-on Workshop
Show steps
Enhance practical skills and gain hands-on experience with Vertex AI.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- Attend a hands-on workshop focused on Vertex AI.
- Build and deploy a machine learning model using Vertex AI services.
Image Classification Model Report
Show steps
Demonstrate understanding of model development and evaluation by creating a comprehensive report.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- Train and evaluate the image classification model.
- Analyze the model's performance and identify areas for improvement.
- Write a detailed report summarizing the model development process, results, and insights.
Kaggle Image Classification Competition
Show steps
Challenge and test the limits of understanding through a competitive environment.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- Explore Kaggle competitions related to image classification.
- Select a competition and build a submission using TensorFlow.
Career center
Learners who complete Running Distributed TensorFlow using Vertex AI will develop knowledge and skills
that may be useful to these careers:
TensorFlow Developer
TensorFlow Developer
TensorFlow Developers work on research and development projects that use the TensorFlow platform. They may also contribute to the TensorFlow codebase itself. This course will help you build a foundation in TensorFlow and its distribution strategies, which are essential for developing high-performance machine learning models. You will also learn how to use the Vertex AI platform to train and deploy your models.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers use their knowledge of machine learning algorithms and techniques to design, build, and deploy machine learning models. This course will help you build a foundation in TensorFlow and its distribution strategies, which are essential for developing high-performance machine learning models. You will also learn how to use the Vertex AI platform to train and deploy your models.
Data Scientist
Data Scientist
Data Scientists use their knowledge of statistics, mathematics, and computer science to extract insights from data. They may also use machine learning algorithms to build predictive models. This course will help you build a foundation in TensorFlow and its distribution strategies, which are essential for developing high-performance machine learning models. You will also learn how to use the Vertex AI platform to train and deploy your models.
AI Engineer
AI Engineer
AI Engineers use their knowledge of artificial intelligence and machine learning to design, build, and deploy AI systems. This course will help you build a foundation in TensorFlow and its distribution strategies, which are essential for developing high-performance machine learning models. You will also learn how to use the Vertex AI platform to train and deploy your models.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. They may also work on research and development projects. This course will help you build a foundation in TensorFlow and its distribution strategies, which are essential for developing high-performance machine learning models. You will also learn how to use the Vertex AI platform to train and deploy your models.
Cloud Architect
Cloud Architect
Cloud Architects design and manage cloud computing systems. They may also work on research and development projects. This course will help you build a foundation in TensorFlow and its distribution strategies, which are essential for developing high-performance machine learning models. You will also learn how to use the Vertex AI platform to train and deploy your models.
Data Analyst
Data Analyst
Data Analysts use their knowledge of statistics, mathematics, and computer science to extract insights from data. They may also use machine learning algorithms to build predictive models. This course may be helpful for you if you want to learn more about TensorFlow and its distribution strategies.
Business Analyst
Business Analyst
Business Analysts use their knowledge of business and technology to identify and solve business problems. They may also work on research and development projects. This course may be helpful for you if you want to learn more about TensorFlow and its distribution strategies.
Product Manager
Product Manager
Product Managers work with engineers and designers to define and develop new products. They may also work on research and development projects. This course may be helpful for you if you want to learn more about TensorFlow and its distribution strategies.
Project Manager
Project Manager
Project Managers plan and manage projects. They may also work on research and development projects. This course may be helpful for you if you want to learn more about TensorFlow and its distribution strategies.
Sales Engineer
Sales Engineer
Sales Engineers work with customers to identify and solve their business problems. They may also work on research and development projects. This course may be helpful for you if you want to learn more about TensorFlow and its distribution strategies.
Technical Writer
Technical Writer
Technical Writers create and edit documentation for software and hardware products. They may also work on research and development projects. This course may be helpful for you if you want to learn more about TensorFlow and its distribution strategies.
Customer Success Manager
Customer Success Manager
Customer Success Managers work with customers to ensure that they are satisfied with their products and services. They may also work on research and development projects. This course may be helpful for you if you want to learn more about TensorFlow and its distribution strategies.
Recruiter
Recruiter
Recruiters find and hire new employees for companies. They may also work on research and development projects. This course may be helpful for you if you want to learn more about TensorFlow and its distribution strategies.
Administrative Assistant
Administrative Assistant
Administrative Assistants provide administrative support to managers and other employees. They may also work on research and development projects. This course is not likely to be helpful for you if you are interested in pursuing a career as an Administrative Assistant.
For more career information including salaries, visit:
OpenCourser.com/course/4nk3ug/running
Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Running Distributed TensorFlow using Vertex AI.
Provides a comprehensive overview of pattern recognition and machine learning. It covers various techniques for data analysis, classification, and regression, providing a solid foundation for understanding machine learning algorithms.
Covers the latest advancements in TensorFlow 2 and Keras. It provides practical guidance on building and training deep learning models for various tasks, including image classification, natural language processing, and time series forecasting.
Serves as a comprehensive guide to deep learning using Python. It covers various deep learning algorithms and techniques, providing a foundation for building andトレーニングDeep learning models.
Takes readers beyond the basics of deep learning. It explores advanced topics such as advanced neural networks, transfer learning, and reinforcement learning, providing a deeper understanding of deep learning techniques.
Provides a comprehensive overview of TensorFlow, including its history, benefits, and potential applications. It valuable resource for anyone who wants to learn more about TensorFlow and how to use it for deep learning.
Provides a comprehensive overview of deep learning, including its history, benefits, and potential applications. It valuable resource for anyone who wants to learn more about deep learning and how to use it for a variety of tasks.
Focuses on handling and preparing data for machine learning models. It explores best practices for data preprocessing, data cleaning, and managing large datasets using TensorFlow.
Provides a comprehensive overview of machine learning, including its history, benefits, and potential applications. It valuable resource for anyone who wants to learn more about machine learning and how to use it for a variety of tasks.
Provides a comprehensive overview of statistical learning, including its history, benefits, and potential applications. It valuable resource for anyone who wants to learn more about statistical learning and how to use it for a variety of tasks.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/4nk3ug/running
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Effort
1 hour 30 minutes
Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Good to know
Specializes in helping learners develop skills and knowledge in training machine learning models and deploying them on the Vertex AI platform
Offers an up-to-date exploration of training and deploying custom image classification models with TensorFlow's distribution strategies
Provides a self-paced, hands-on learning experience through the Google Cloud console
Led by Google Cloud Training, known for its expertise in training and deploying machine learning models
The course is appropriate for learners with some prior knowledge in machine learning, TensorFlow, and cloud computing
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