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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 create a computer vision model that can recognize items of clothing and then explore what affects the training model.
Register for this course and see more details by visiting:
OpenCourser.com/course/02b3oh/introduction
What's inside
Syllabus
Introduction to Computer Vision with TensorFlow
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
This course offers a strong foundation in Computer Vision with TensorFlow
Taught by Google Cloud Training, who are recognized for their work in Computer Vision
Well-suited for learners interested in Computer Vision
Builds a strong foundation in Computer Vision
Develops practical skills in creating and training Computer Vision models
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Save Introduction to Computer Vision with TensorFlow 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 Introduction to Computer Vision with TensorFlow with these
activities:
Organize and expand your course materials
Show steps
Enhance your understanding of the course material by organizing and supplementing your notes, assignments, and other resources, creating a comprehensive study aid.
Show steps
-
Compile all course materials into a central location.
-
Review and summarize key concepts from each unit.
-
Identify areas where additional research or clarification is needed.
Review the fundamentals of computer vision
Show steps
Strengthen your foundation in computer vision by revisiting key concepts and methodologies, enhancing your ability to fully grasp the course material.
Browse courses on
Computer Vision
Show steps
-
Review textbooks or online resources on computer vision.
-
Complete practice problems or exercises related to computer vision.
-
Attend a refresher course or workshop on computer vision.
Refine your understanding of machine learning models
Show steps
Enhance your knowledge of how machine learning models work to fully engage with the course materials.
Browse courses on
Machine Learning
Show steps
-
Review online tutorials on machine learning models.
-
Work through practice problems on machine learning models.
-
Attend a workshop on machine learning models.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Practice creating and training computer vision models
Show steps
Gain practical experience in building and fine-tuning computer vision models to enhance your understanding of the course concepts.
Show steps
-
Complete the hands-on labs provided in the course.
-
Develop a personal project involving computer vision.
-
Participate in online coding challenges focused on computer vision.
Explore advanced computer vision techniques
Show steps
Deepen your knowledge of computer vision by delving into specialized techniques, expanding your understanding beyond the course scope.
Browse courses on
Object Detection
Show steps
-
Follow online tutorials on advanced computer vision techniques.
-
Read research papers on computer vision.
-
Attend conferences and workshops on computer vision.
Attend computer vision meetups and conferences
Show steps
Expand your network and gain insights from experts in the field by attending industry events, fostering connections that can enhance your learning.
Show steps
-
Research upcoming computer vision meetups and conferences.
-
Attend events and actively participate in discussions.
-
Connect with speakers, attendees, and potential mentors.
Design and implement a computer vision solution
Show steps
Apply the knowledge gained in the course to solve a real-world problem using computer vision, solidifying your understanding and skills.
Show steps
-
Identify a problem that can be addressed with computer vision.
-
Design and develop a computer vision solution.
-
Deploy and evaluate your solution.
Contribute to open-source computer vision projects
Show steps
Engage with the wider computer vision community by contributing to open-source projects, gaining valuable hands-on experience and expanding your knowledge.
Show steps
-
Identify open-source computer vision projects that align with your interests.
-
Contribute code, documentation, or bug fixes to the projects.
-
Collaborate with other contributors and learn from their expertise.
Mentor junior computer vision enthusiasts
Show steps
Reinforce your understanding of the course material by assisting others in their learning journey, while also contributing to the community.
Show steps
-
Volunteer as a mentor in online forums or communities.
-
Provide guidance to students or junior developers in computer vision.
-
Create tutorials or documentation to share your knowledge.
Organize and expand your course materials
Show steps
Enhance your understanding of the course material by organizing and supplementing your notes, assignments, and other resources, creating a comprehensive study aid.
Show steps
Show steps
Show steps
- Compile all course materials into a central location.
- Review and summarize key concepts from each unit.
- Identify areas where additional research or clarification is needed.
Review the fundamentals of computer vision
Show steps
Strengthen your foundation in computer vision by revisiting key concepts and methodologies, enhancing your ability to fully grasp the course material.
Browse courses on
Computer Vision
Show steps
Show steps
Show steps
- Review textbooks or online resources on computer vision.
- Complete practice problems or exercises related to computer vision.
- Attend a refresher course or workshop on computer vision.
Refine your understanding of machine learning models
Show steps
Enhance your knowledge of how machine learning models work to fully engage with the course materials.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Review online tutorials on machine learning models.
- Work through practice problems on machine learning models.
- Attend a workshop on machine learning models.
Six other activities
Expand to see all activities and additional details
Show all nine activities
Practice creating and training computer vision models
Show steps
Gain practical experience in building and fine-tuning computer vision models to enhance your understanding of the course concepts.
Show steps
Show steps
Show steps
- Complete the hands-on labs provided in the course.
- Develop a personal project involving computer vision.
- Participate in online coding challenges focused on computer vision.
Explore advanced computer vision techniques
Show steps
Deepen your knowledge of computer vision by delving into specialized techniques, expanding your understanding beyond the course scope.
Browse courses on
Object Detection
Show steps
Show steps
Show steps
- Follow online tutorials on advanced computer vision techniques.
- Read research papers on computer vision.
- Attend conferences and workshops on computer vision.
Attend computer vision meetups and conferences
Show steps
Expand your network and gain insights from experts in the field by attending industry events, fostering connections that can enhance your learning.
Show steps
Show steps
Show steps
- Research upcoming computer vision meetups and conferences.
- Attend events and actively participate in discussions.
- Connect with speakers, attendees, and potential mentors.
Design and implement a computer vision solution
Show steps
Apply the knowledge gained in the course to solve a real-world problem using computer vision, solidifying your understanding and skills.
Show steps
Show steps
Show steps
- Identify a problem that can be addressed with computer vision.
- Design and develop a computer vision solution.
- Deploy and evaluate your solution.
Contribute to open-source computer vision projects
Show steps
Engage with the wider computer vision community by contributing to open-source projects, gaining valuable hands-on experience and expanding your knowledge.
Show steps
Show steps
Show steps
- Identify open-source computer vision projects that align with your interests.
- Contribute code, documentation, or bug fixes to the projects.
- Collaborate with other contributors and learn from their expertise.
Mentor junior computer vision enthusiasts
Show steps
Reinforce your understanding of the course material by assisting others in their learning journey, while also contributing to the community.
Show steps
Show steps
Show steps
- Volunteer as a mentor in online forums or communities.
- Provide guidance to students or junior developers in computer vision.
- Create tutorials or documentation to share your knowledge.
Career center
Learners who complete Introduction to Computer Vision with TensorFlow will develop knowledge and skills
that may be useful to these careers:
Computer Vision Consultant
Computer Vision Consultant
A Computer Vision Consultant provides advice and guidance to organizations on how to use computer vision technology. This course may be useful for those who want to enter or advance their career in the field of computer vision by giving them a basic understanding of the field and skills required to provide consulting services.
Research Scientist
Research Scientist
A Research Scientist conducts research in a specific field of science. This course may be useful for Research Scientists who want to specialize in the field of computer vision by giving them a basic understanding of the field and skills required to conduct research in computer vision.
Data Scientist
Data Scientist
A Data Scientist combines programming skills with knowledge of mathematics and statistics to extract insights from data. This course may be useful for Data Scientists who want to specialize in the field of computer vision by giving them a basic understanding of the field and skills required to train computer vision models.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer is responsible for developing and deploying machine learning models. This course may be useful for Machine Learning Engineers who want to specialize in the field of computer vision by giving them a basic understanding of the field and skills required to train computer vision models.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
An Artificial Intelligence Engineer designs and develops artificial intelligence systems. This course may be useful for Artificial Intelligence Engineers who want to specialize in the field of computer vision by giving them a basic understanding of the field and skills required to train computer vision models.
UX Designer
UX Designer
A UX Designer designs user interfaces for products and services. This course may be useful for UX Designers who want to specialize in the field of computer vision by giving them a basic understanding of the field and skills required to design user interfaces for computer vision products and services.
Computer Vision Engineer
Computer Vision Engineer
A Computer Vision Engineer designs, develops, and deploys computer vision systems. Computer vision is a subfield of artificial intelligence that enables computers and systems to derive meaningful information from digital images, videos, and other visual inputs. This course may be useful for those who want to enter or advance their career in the field of computer vision by giving them a basic understanding of the fundamentals of the field and skills required to build models that can recognize objects in images.
Sales Engineer
Sales Engineer
A Sales Engineer provides technical support to customers and helps them to choose the right products and services. This course may be useful for Sales Engineers who want to specialize in the field of computer vision by giving them a basic understanding of the field and skills required to provide technical support and help customers choose the right computer vision products and services.
Quality Assurance Analyst
Quality Assurance Analyst
A Quality Assurance Analyst tests software products and services to ensure that they meet quality standards. This course may be useful for Quality Assurance Analysts who want to specialize in the field of computer vision by giving them a basic understanding of the field and skills required to test computer vision products and services.
Marketing Manager
Marketing Manager
A Marketing Manager is responsible for developing and executing marketing campaigns. This course may be useful for Marketing Managers who want to specialize in the field of computer vision by giving them a basic understanding of the field and skills required to develop and execute marketing campaigns for computer vision products and services.
Project Manager
Project Manager
A Project Manager is responsible for planning, executing, and closing projects. This course may be useful for Project Managers who want to specialize in the field of computer vision by giving them a basic understanding of the field and skills required to plan, execute, and close computer vision projects.
Business Analyst
Business Analyst
A Business Analyst analyzes business processes and systems. This course may be useful for Business Analysts who want to specialize in the field of computer vision by giving them a basic understanding of the field and skills required to analyze business processes and systems that use computer vision technology.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course may be useful for Software Engineers who want to specialize in the field of computer vision by giving them a basic understanding of the field and skills required to build computer vision applications.
Product Manager
Product Manager
A Product Manager is responsible for the development and marketing of a product. This course may be useful for Product Managers who want to specialize in the field of computer vision by giving them a basic understanding of the field and skills required to develop and market computer vision products.
Technical Writer
Technical Writer
A Technical Writer creates documentation for technical products and services. This course may be useful for Technical Writers who want to specialize in the field of computer vision by giving them a basic understanding of the field and skills required to create documentation for computer vision products and services.
For more career information including salaries, visit:
OpenCourser.com/course/02b3oh/introduction
Reading list
We've selected seven 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 Computer Vision with TensorFlow.
Save
Provides a comprehensive overview of deep learning for computer vision, covering topics such as convolutional neural networks, recurrent neural networks, and transformers.
This online course provides a practical introduction to deep learning for computer vision applications, covering topics such as image classification, object detection, and image segmentation.
Provides a practical guide to using Python for computer vision tasks, covering topics such as image processing, object detection, and image segmentation.
Provides a practical introduction to deep learning for computer vision, covering the basics of image processing, convolutional neural networks, and object detection.
This textbook provides a comprehensive overview of computer vision, covering topics such as image processing, feature extraction, and object recognition.
Save
This textbook provides a comprehensive overview of computer vision algorithms and applications, covering topics such as image formation, feature extraction, and object recognition.
Provides a comprehensive overview of pattern recognition and machine learning, covering topics such as statistical learning, support vector machines, and neural networks.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/02b3oh/introduction
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Effort
1 hour
Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Good to know
This course offers a strong foundation in Computer Vision with TensorFlow
Taught by Google Cloud Training, who are recognized for their work in Computer Vision
Well-suited for learners interested in Computer Vision
Builds a strong foundation in Computer Vision
Develops practical skills in creating and training Computer Vision models
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