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Serving Tensorflow Models with a REST API
Charles Ivan Niswander II
Charles Ivan Niswander II
In this project-based course, you will learn step-by-step procedures for serving Tensorflow models with a RESTful API.
We will learn to save a Tensorflow object as a servable, deploy servables in Docker containers, as well as how to test our API endpoints...
Read more
In this project-based course, you will learn step-by-step procedures for serving Tensorflow models with a RESTful API.
We will learn to save a Tensorflow object as a servable, deploy servables in Docker containers, as well as how to test our API endpoints...
Read more
In this project-based course, you will learn step-by-step procedures for serving Tensorflow models with a RESTful API.
We will learn to save a Tensorflow object as a servable, deploy servables in Docker containers, as well as how to test our API endpoints and optimize our API response time.
I would encourage learners to experiment with the tools and methods discussed in this course. The learner is highly encouraged to experiment beyond the scope of the course.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/5irz72/serving
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Appropriate for North American-based learners
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Reviews summary
Tutorial recreation
This course has a single 2-star review indicating that it mostly only covers material that is already found in tutorials and reproduced from other content on the web.
Mostly a recreation of a known tutorial.
"Terrible course!!Why author copy paste tutorial ?"
Activities
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We're preparing activities for
Serving Tensorflow Models with a REST API.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Serving Tensorflow Models with a REST API will develop knowledge and skills
that may be useful to these careers:
Software Engineer
Software Engineer
Software Engineers are responsible for researching, developing, and testing software. They write and maintain the code that makes software programs work. This course can help Software Engineers to learn how to serve Tensorflow models with a REST API, which is a valuable skill in the field of software development.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for developing and implementing machine learning models. They work with data scientists to identify and solve business problems using machine learning. This course can help Machine Learning Engineers to learn how to serve Tensorflow models with a REST API, which is a valuable skill in the field of machine learning.
Data Scientist
Data Scientist
Data Scientists are responsible for collecting, cleaning, and analyzing data to extract insights. They use their findings to solve business problems and make informed decisions. This course can help Data Scientists to learn how to serve Tensorflow models with a REST API, which is a valuable skill in the field of data science.
DevOps Engineer
DevOps Engineer
DevOps Engineers are responsible for bridging the gap between development and operations teams. They work to ensure that software is deployed and maintained efficiently. This course can help DevOps Engineers to learn how to serve Tensorflow models with a REST API, which is a valuable skill in the field of DevOps.
Cloud Architect
Cloud Architect
Cloud Architects are responsible for designing and implementing cloud computing solutions. They work with clients to identify their needs and develop solutions that meet their requirements. This course can help Cloud Architects to learn how to serve Tensorflow models with a REST API, which is a valuable skill in the field of cloud computing.
Full-Stack Developer
Full-Stack Developer
Full Stack Developers are responsible for developing both the front-end and back-end of software applications. They work with a variety of technologies to create and maintain software products. This course can help Full Stack Developers to learn how to serve Tensorflow models with a REST API, which is a valuable skill in the field of software development.
Front-End Developer
Front-End Developer
Front-End Developers are responsible for developing the user interface of software applications. They work with designers to create and maintain the look and feel of software products. This course may be useful for Front-End Developers who are interested in learning more about serving Tensorflow models with a REST API.
Back-End Developer
Back-End Developer
Back-End Developers are responsible for developing the server-side of software applications. They work with databases and other technologies to create and maintain the functionality of software products. This course may be useful for Back-End Developers who are interested in learning more about serving Tensorflow models with a REST API.
Database Administrator
Database Administrator
Database Administrators are responsible for managing and maintaining databases. They work with database software and hardware to ensure that data is stored and accessed efficiently. This course may be useful for Database Administrators who are interested in learning more about serving Tensorflow models with a REST API.
System Administrator
System Administrator
System Administrators are responsible for managing and maintaining computer systems. They work with hardware and software to ensure that systems are running smoothly and efficiently. This course may be useful for System Administrators who are interested in learning more about serving Tensorflow models with a REST API.
Network Administrator
Network Administrator
Network Administrators are responsible for managing and maintaining computer networks. They work with hardware and software to ensure that networks are running smoothly and efficiently. This course may be useful for Network Administrators who are interested in learning more about serving Tensorflow models with a REST API.
Security Analyst
Security Analyst
Security Analysts are responsible for protecting computer systems from security threats. They work with software and hardware to identify and mitigate security risks. This course may be useful for Security Analysts who are interested in learning more about serving Tensorflow models with a REST API.
IT Manager
IT Manager
IT Managers are responsible for managing and directing IT departments. They work with other managers to ensure that IT systems are aligned with business goals. This course may be useful for IT Managers who are interested in learning more about serving Tensorflow models with a REST API.
CIO
CIO
CIOs are responsible for leading IT organizations. They work with other executives to ensure that IT is aligned with business strategy. This course may be useful for CIOs who are interested in learning more about serving Tensorflow models with a REST API.
CTO
CTO
CTOs are responsible for leading technology organizations. They work with other executives to ensure that technology is aligned with business strategy. This course may be useful for CTOs who are interested in learning more about serving Tensorflow models with a REST API.
For more career information including salaries, visit:
OpenCourser.com/course/5irz72/serving
Reading list
We've selected ten 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
Serving Tensorflow Models with a REST API.
This second edition of the popular Deep Learning with Python has been revised to include the latest developments and best practices in the field of deep learning.
This hands-on guide to deep learning with Python is widely used by academic institutions and industry professionals, this user-friendly text provides thorough coverage of neural networks, deep learning techniques, and best practices.
Is ideal for those who want to gain a deep understanding of the theoretical underpinnings of deep learning.
This easy-to-follow, comprehensive guide is helpful for learners new to Tensorflow and can be used as a handy handbook once learners have completed the course.
A more in-depth examination of machine learning, this text covers the mechanics of machine learning, common algorithms and models, and practical implementation.
This highly visual book provides a comprehensive overview of deep learning, making it a great choice for beginners.
Focuses on computer vision applications using TensorFlow 2.0.
Provides an in-depth look at probabilistic machine learning, which subfield of machine learning that uses probability theory to model data.
For those interested in reinforcement learning, this book provides a comprehensive introduction to the topic.
Save
TensorFlow can be used with other languages besides Python and this book provides detailed explanations of how to use R with TensorFlow.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/5irz72/serving
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