Deploy Models with TensorFlow Serving and Flask from Coursera

In this 2-hour long project-based course, you will learn how to deploy TensorFlow models using TensorFlow Serving and Docker, and you will create a simple web application with Flask which will serve as an interface to get predictions from the served TensorFlow model.

This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your Internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with (e.g. Python, Jupyter, and Tensorflow) pre-installed.

Prerequisites:

In order to be successful in this project, you should be familiar with Python, TensorFlow, Flask, and HTML.

Notes:

- You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want.

- 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.

What's inside

Syllabus

Deploy Models with TensorFlow Serving and Flask

Welcome to this project-based course on Deploying Models with TensorFlow Serving and Flask. In this project, we will deploy a TensorFlow model with the help of TensorFlow Serving, and we will create a small web app which will serve as a visual interface to the model inference. TensorFlow Serving is the ideal way to serve TensorFlow models in production, and Flask is a minimal web framework which lets developers create web apps really quickly.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches TensorFlow Serving and Flask, two tools that are essential for production model deployment

Covers the entire lifecycle of model development and deployment

Provides hands-on experience via Google's Rhyme platform

Requires knowledge of Python, TensorFlow, and HTML

Works best for learners in the North America region

Reviews summary

Tensorflow serving and flask basic deployment course

Learners say this basic course on deploying models with TensorFlow Serving and Flask is a good starting point for beginners looking to get into this field. Students describe lectures as easy to follow and well-paced, and they especially enjoyed the hands-on project. However, some learners express that information on the topics could be more in-depth, and they would have liked to see more coverage of TensorFlow Serving.

Beginner-friendly

"Nice way to get started with model deployment with web app."

"Great hands-on tutorial for beginners"

Features a hands-on project

"EXCELLENT"

"Great hands-on tutorial for beginners"

"really good effort to breakdown the complete process and make it easy to understand"

Virtual machine has limitations

"Time given for the virtual desktop is not enought if you actually type and try everything he does."

"The virtual machine could be properly configured so as not to waste time on problems that arise."

"Without Jupiter Netbook it's rather hard to follow."

Lacks in-depth coverage

"Only one video demo with no relation to real-life application"

"I am afriad this presentation really doent work as a format"

"The course is too basic"

"As a potential for improvement I would like to propose more coverage of TensorFlow Service itself"

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 Deploy Models with TensorFlow Serving and Flask with these activities:

Review Python Fundamentals

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Brush up on the basics of Python to enhance your understanding of the course material.

Browse courses on Python Basics

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Review Python syntax and data structures
Practice writing simple Python programs

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

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Gain additional insights by reading a relevant book on machine learning with TensorFlow.

View Hands-On Machine Learning with Scikit-Learn,... on Amazon

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Read chapters relevant to the course material

Course Material Notes Compilation

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Improve your understanding by compiling and reviewing key course notes.

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Gather and organize course notes, slides, and readings
Review and summarize the compiled materials

Four other activities

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Show all seven activities

Peer Study Group Discussions

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Engage with peers to discuss course concepts, share knowledge, and offer support.

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Join or create a peer study group
Actively participate in group discussions

TensorFlow Serving and Docker Tutorials

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Enhance your understanding by following guided tutorials on TensorFlow Serving and Docker.

Browse courses on TensorFlow Serving

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Complete a TensorFlow Serving tutorial
Complete a Docker tutorial

TensorFlow Model Deployment Blog Post

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Solidify your understanding by creating a blog post that explains how to deploy TensorFlow models.

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Research and gather information on TensorFlow model deployment
Write a comprehensive blog post covering the deployment process

TensorFlow Model Deployment Project

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Apply your skills by deploying a TensorFlow model as part of a larger project.

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Define the project scope and objectives
Gather and prepare the necessary data
Train and deploy the TensorFlow model
Evaluate the performance of the deployed model

Career center

Learners who complete Deploy Models with TensorFlow Serving and Flask will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

TensorFlow Serving and Flask are essential tools for machine learning engineers who want to deploy machine learning models into production. This course will teach you how to use these technologies to create a web application that can serve predictions from your TensorFlow models. As a machine learning engineer, you will need to be able to deploy models into production in order to make them useful to end users. This course will give you the skills you need to do that.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

TensorFlow Serving and Flask are essential tools for data scientists who want to deploy machine learning models into production. This course will teach you how to use these technologies to create a web application that can serve predictions from your TensorFlow models. As a data scientist, you will need to be able to deploy models into production in order to make them useful to end users. This course will give you the skills you need to do that.

See salaries and explore the career path for Data Scientist

Software Engineer

TensorFlow Serving and Flask are essential tools for software engineers who want to deploy machine learning models into production. This course will teach you how to use these technologies to create a web application that can serve predictions from your TensorFlow models. As a software engineer, you will need to be able to deploy models into production in order to make them useful to end users. This course will give you the skills you need to do that.

See salaries and explore the career path for Software Engineer

Data Engineer

TensorFlow Serving and Flask are essential tools for data engineers who want to deploy machine learning models into production. This course will teach you how to use these technologies to create a web application that can serve predictions from your TensorFlow models. As a data engineer, you will need to be able to deploy models into production in order to make them useful to end users. This course will give you the skills you need to do that.

See salaries and explore the career path for Data Engineer

Data Analyst

TensorFlow Serving and Flask are essential tools for data analysts who want to deploy machine learning models into production. This course will teach you how to use these technologies to create a web application that can serve predictions from your TensorFlow models. As a data analyst, you will need to be able to deploy models into production in order to make them useful to end users. This course will give you the skills you need to do that.

See salaries and explore the career path for Data Analyst

Web Developer

TensorFlow Serving and Flask are essential tools for web developers who want to deploy machine learning models into production. This course will teach you how to use these technologies to create a web application that can serve predictions from your TensorFlow models. As a web developer, you will need to be able to deploy models into production in order to make them useful to end users. This course will give you the skills you need to do that.

See salaries and explore the career path for Web Developer

DevOps Engineer

TensorFlow Serving and Flask are essential tools for DevOps engineers who want to deploy machine learning models into production. This course will teach you how to use these technologies to create a web application that can serve predictions from your TensorFlow models. As a DevOps engineer, you will need to be able to deploy models into production in order to make them useful to end users. This course will give you the skills you need to do that.

See salaries and explore the career path for DevOps Engineer

Cloud Architect

TensorFlow Serving and Flask are essential tools for cloud architects who want to deploy machine learning models into production. This course will teach you how to use these technologies to create a web application that can serve predictions from your TensorFlow models. As a cloud architect, you will need to be able to deploy models into production in order to make them useful to end users. This course will give you the skills you need to do that.

See salaries and explore the career path for Cloud Architect

Product Manager

TensorFlow Serving and Flask are essential tools for product managers who want to deploy machine learning models into production. This course will teach you how to use these technologies to create a web application that can serve predictions from your TensorFlow models. As a product manager, you will need to be able to deploy models into production in order to make them useful to end users. This course will give you the skills you need to do that.

See salaries and explore the career path for Product Manager

Data Visualization Engineer

TensorFlow Serving and Flask are essential tools for data visualization engineers who want to deploy machine learning models into production. This course will teach you how to use these technologies to create a web application that can serve predictions from your TensorFlow models. As a data visualization engineer, you will need to be able to deploy models into production in order to make them useful to end users. This course will give you the skills you need to do that.

See salaries and explore the career path for Data Visualization Engineer

Business Analyst

TensorFlow Serving and Flask are essential tools for business analysts who want to deploy machine learning models into production. This course will teach you how to use these technologies to create a web application that can serve predictions from your TensorFlow models. As a business analyst, you will need to be able to deploy models into production in order to make them useful to end users. This course will give you the skills you need to do that.

See salaries and explore the career path for Business Analyst

UX Designer

TensorFlow Serving and Flask are essential tools for UX designers who want to deploy machine learning models into production. This course will teach you how to use these technologies to create a web application that can serve predictions from your TensorFlow models. As a UX designer, you will need to be able to deploy models into production in order to make them useful to end users. This course will give you the skills you need to do that.

See salaries and explore the career path for UX Designer

Technical Writer

TensorFlow Serving and Flask are essential tools for technical writers who want to deploy machine learning models into production. This course will teach you how to use these technologies to create a web application that can serve predictions from your TensorFlow models. As a technical writer, you will need to be able to deploy models into production in order to make them useful to end users. This course will give you the skills you need to do that.

See salaries and explore the career path for Technical Writer

IT Support Specialist

TensorFlow Serving and Flask are essential tools for IT support specialists who want to deploy machine learning models into production. This course will teach you how to use these technologies to create a web application that can serve predictions from your TensorFlow models. As an IT support specialist, you will need to be able to deploy models into production in order to make them useful to end users. This course will give you the skills you need to do that.

See salaries and explore the career path for IT Support Specialist

Teacher

TensorFlow Serving and Flask are essential tools for teachers who want to deploy machine learning models into production. This course will teach you how to use these technologies to create a web application that can serve predictions from your TensorFlow models. As a teacher, you will need to be able to deploy models into production in order to make them useful to your students. This course will give you the skills you need to do that.

See salaries and explore the career path for Teacher