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Introduction to TensorFlow Lite

Daniel Situnayake, Paige Bailey, and Juan Delgado

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What's inside

Syllabus

Welcome to the course!

Learn how TensorFlow Lite works under the hood.

Learn how to deploy TensorFlow Lite models on Android.

Learn how to deploy TensorFlow Lite models on iOS.

Learn how to deploy TensorFlow Lite models on IoT devices.

Congratulations! You've reached the end of the course.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Builds a strong foundation for beginners who want to deploy deep learning models on mobile and embedded devices

Taught by Daniel Situnayake, Paige Bailey, and Juan Delgado, who are recognized experts in TensorFlow Lite development

Examines TensorFlow Lite, which is highly relevant to mobile and embedded device development

Offers hands-on labs and interactive materials to reinforce learning

Multi-modal, including videos, readings, and discussions

Provides a comprehensive study of TensorFlow Lite deployment

Save this course

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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 Introduction to TensorFlow Lite with these activities:

Review key concepts in machine learning

Show steps

This activity will help you refresh your memory of key concepts in machine learning, which will make it easier to understand the material in this course.

Browse courses on Machine Learning

Show steps

Read through your notes or textbooks from previous machine learning courses.
Review online resources, such as articles or videos, on machine learning.
Take a practice quiz or exam to test your understanding.

Follow tutorials on how to use TensorFlow Lite

Show steps

This activity will help you learn how to use TensorFlow Lite to deploy deep learning models on mobile and embedded devices.

Browse courses on TensorFlow Lite

Show steps

Find a tutorial on how to use TensorFlow Lite.
Follow the steps in the tutorial.
Test your TensorFlow Lite model on a mobile or embedded device.

Attend a workshop on TensorFlow Lite

Show steps

This activity will help you learn more about TensorFlow Lite and get hands-on experience with the technology.

Browse courses on TensorFlow Lite

Show steps

Find a workshop on TensorFlow Lite.
Attend the workshop.
Follow along with the instructor and complete the exercises.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Solve practice problems on deploying deep learning models

Show steps

This activity will help you practice deploying deep learning models on mobile and embedded devices.

Browse courses on TensorFlow Lite

Show steps

Find a set of practice problems on deploying deep learning models.
Solve the practice problems.
Check your answers against the solutions provided.

Start a personal project using TensorFlow Lite

Show steps

This activity will help you apply your knowledge of TensorFlow Lite to a personal project.

Browse courses on TensorFlow Lite

Show steps

Come up with an idea for a personal project that could use TensorFlow Lite.
Develop a project plan.
Start working on the project.

Create a mobile or embedded application that uses TensorFlow Lite

Show steps

This activity will help you apply your knowledge of TensorFlow Lite to a real-world project.

Browse courses on TensorFlow Lite

Show steps

Come up with an idea for a mobile or embedded application that could use TensorFlow Lite.
Develop the application using TensorFlow Lite.
Test the application on a mobile or embedded device.

Contribute to an open-source project related to TensorFlow Lite

Show steps

This activity will help you learn more about TensorFlow Lite and contribute to the community.

Browse courses on TensorFlow Lite

Show steps

Find an open-source project related to TensorFlow Lite that you are interested in.
Read the project documentation.
Start contributing to the project.

Career center

Learners who complete Introduction to TensorFlow Lite will develop knowledge and skills that may be useful to these careers:

Software Developer

Software Developers create, deploy, and maintain applications and software systems. They work on the programming, design, and deployment phases of the lifecycle of an application and may carry out all aspects of the process. To become a Software Developer, you will typically need at least a bachelor's degree in computer science, software engineering, or a related field. A solid understanding of TensorFlow Lite can help Software Developers to create, test, and deploy models on mobile and embedded devices, which is a valuable skill in the industry.

See salaries and explore the career path for Software Developer

Machine Learning Engineer

Machine Learning Engineers are responsible for designing, developing, testing, and deploying machine learning models. They work on a variety of projects, such as developing algorithms for image recognition, natural language processing, and speech recognition. To become a Machine Learning Engineer, you will typically need at least a bachelor's degree in computer science, mathematics, or a related field. Introduction to TensorFlow Lite can help Machine Learning Engineers to gain hands-on experience with deploying models on mobile and embedded devices, which is becoming increasingly important as these devices become more powerful.

See salaries and explore the career path for Machine Learning Engineer

Deep Learning Engineer

Deep Learning Engineers design, develop, and implement deep learning models. They work on various projects, such as developing models for image recognition, natural language processing, and speech recognition. To become a Deep Learning Engineer, you will typically need at least a bachelor's degree in computer science, mathematics, or a related field. Introduction to TensorFlow Lite can prove particularly beneficial to Deep Learning Engineers, since TensorFlow Lite enables Deep Learning Engineers to deploy models on mobile and embedded devices, which opens up new possibilities for applications.

See salaries and explore the career path for Deep Learning Engineer

Data Scientist

Data Scientists are responsible for collecting, cleaning, and analyzing data. They use their findings to develop machine learning models and other data-driven solutions. To become a Data Scientist, you will typically need at least a bachelor's degree in computer science, mathematics, or a related field. A course on TensorFlow Lite may be helpful for Data Scientists who want to learn how to deploy models on mobile and embedded devices.

See salaries and explore the career path for Data Scientist

Quantitative Analyst

Quantitative Analysts (Quants) use mathematical and statistical models to analyze data and make predictions. They work in a variety of industries, such as finance, insurance, and healthcare. To become a Quant, you will typically need at least a bachelor's degree in mathematics, statistics, or a related field. Introduction to TensorFlow Lite can provide Quants with valuable knowledge about deploying models on mobile and embedded devices, which is especially useful for developing trading algorithms and other real-time applications.

See salaries and explore the career path for Quantitative Analyst

Systems Engineer

Systems Engineers design, develop, and maintain computer systems. They work on a variety of projects, such as developing operating systems, networking systems, and cloud computing systems. To become a Systems Engineer, you will typically need at least a bachelor's degree in computer science, software engineering, or a related field. Introduction to TensorFlow Lite can prove beneficial for Systems Engineers who work on developing embedded systems or deploying machine learning models on edge devices.

See salaries and explore the career path for Systems Engineer

Mobile Developer

Mobile Developers design, develop, and maintain mobile applications. They work on a variety of projects, such as developing apps for smartphones, tablets, and wearables. To become a Mobile Developer, you will typically need at least a bachelor's degree in computer science, software engineering, or a related field. Introduction to TensorFlow Lite can help Mobile Developers learn how to deploy machine learning models on mobile devices, which is becoming increasingly important as more and more mobile devices are used for everyday tasks.

See salaries and explore the career path for Mobile Developer

Embedded Software Engineer

Embedded Software Engineers design, develop, and maintain software for embedded systems. They work on a variety of projects, such as developing software for self-driving cars, medical devices, and industrial automation systems. To become an Embedded Software Engineer, you will typically need at least a bachelor's degree in computer science, software engineering, or a related field. Introduction to TensorFlow Lite is an excellent resource for Embedded Software Engineers who want to learn how to deploy machine learning models on embedded devices.

See salaries and explore the career path for Embedded Software Engineer

Front-End Developer

Front-End Developers design, develop, and maintain the user interface of websites and web applications. They work on a variety of projects, such as developing websites for e-commerce, social media, and news. To become a Front-End Developer, you will typically need at least a bachelor's degree in computer science, web development, or a related field. While Introduction to TensorFlow Lite may not be directly relevant to Front-End Development, it can still be helpful for those who want to learn more about machine learning and how it can be used in web development.

See salaries and explore the career path for Front-End Developer

Back-End Developer

Back-End Developers design, develop, and maintain the server-side of websites and web applications. They work on a variety of projects, such as developing APIs, databases, and cloud computing systems. To become a Back-End Developer, you will typically need at least a bachelor's degree in computer science, software engineering, or a related field. Introduction to TensorFlow Lite may be helpful for Back-End Developers who want to learn more about machine learning and how it can be used in web development.

See salaries and explore the career path for Back-End Developer

Full-Stack Developer

Full-Stack Developers design, develop, and maintain both the front-end and back-end of websites and web applications. They work on a variety of projects, such as developing e-commerce websites, social media platforms, and news websites. To become a Full-Stack Developer, you will typically need at least a bachelor's degree in computer science, web development, or a related field. While Introduction to TensorFlow Lite may not be directly relevant to Full-Stack Development, it can still be helpful for those who want to learn more about machine learning and how it can be used in web development.

See salaries and explore the career path for Full-Stack Developer

Database Administrator

Database Administrators design, develop, and maintain databases. They work on a variety of projects, such as developing databases for e-commerce websites, social media platforms, and news websites. To become a Database Administrator, you will typically need at least a bachelor's degree in computer science, database administration, or a related field. Introduction to TensorFlow Lite may be helpful for Database Administrators who want to learn more about machine learning and how it can be used in database management.

See salaries and explore the career path for Database Administrator

Cloud Architect

Cloud Architects design, develop, and maintain cloud computing systems. They work on a variety of projects, such as developing cloud computing systems for e-commerce websites, social media platforms, and news websites. To become a Cloud Architect, you will typically need at least a bachelor's degree in computer science, cloud computing, or a related field. Introduction to TensorFlow Lite may be helpful for Cloud Architects who want to learn more about machine learning and how it can be used in cloud computing.

See salaries and explore the career path for Cloud Architect

Data Analyst

Data Analysts collect, clean, and analyze data. They use their findings to develop insights and make recommendations. To become a Data Analyst, you will typically need at least a bachelor's degree in computer science, mathematics, or a related field. Introduction to TensorFlow Lite may be helpful for Data Analysts who want to learn more about machine learning and how it can be used in data analysis.

See salaries and explore the career path for Data Analyst

Business Analyst

Business Analysts design, develop, and implement business solutions. They work on a variety of projects, such as developing business solutions for e-commerce websites, social media platforms, and news websites. To become a Business Analyst, you will typically need at least a bachelor's degree in business administration, information systems, or a related field. Introduction to TensorFlow Lite may be helpful for Business Analysts who want to learn more about machine learning and how it can be used in business analysis.

See salaries and explore the career path for Business Analyst

Reading list

We've selected two 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 Introduction to TensorFlow Lite .

Practical Deep Learning for Cloud, Mobile, and Edge

Save

Provides a comprehensive overview of TensorFlow Lite, covering everything from model development to deployment. It valuable resource for anyone who wants to learn more about TensorFlow Lite.

Practical Deep Learning for Cloud, Mobile, and Edge...

Paperback

Practical Deep Learning for Cloud, Mobile, and Edge...

Kindle Edition

Practical Deep Learning for Cloud, Mobile, and Edge

Save

Provides a comprehensive overview of TensorFlow Lite, covering everything from model development to deployment. It valuable resource for anyone who wants to learn more about TensorFlow Lite.

Practical Deep Learning for Cloud, Mobile, and Edge

Paperback

Check price

Practical Deep Learning for Cloud, Mobile, and Edge

Kindle Edition

Check price

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Effort

11 hours

Via

Udacity

Instructors

Daniel Situnayake

Paige Bailey

Juan Delgado

Language

English

Good to know

Builds a strong foundation for beginners who want to deploy deep learning models on mobile and embedded devices

Taught by Daniel Situnayake, Paige Bailey, and Juan Delgado, who are recognized experts in TensorFlow Lite development

Examines TensorFlow Lite, which is highly relevant to mobile and embedded device development

Offers hands-on labs and interactive materials to reinforce learning

Multi-modal, including videos, readings, and discussions

Provides a comprehensive study of TensorFlow Lite deployment

Share and help others discover this course.

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