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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console.
This lab will show you how to install and run an object detection application. The application uses TensorFlow and other public API libraries to detect multiple objects in an uploaded image.
Register for this course and see more details by visiting:
OpenCourser.com/course/yydv3c/creating
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Offers real-world practice through hands-on labs
Focuses on a highly relevant, in-demand skill
Taught by Google Cloud Training, a reputable organization in the tech industry
Suitable for beginners with little to no prior knowledge in object detection
Provides a foundation for further learning in computer vision and deep learning
Save this course
Save Creating an Object Detection Application Using 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 Creating an Object Detection Application Using TensorFlow with these
activities:
Review Computer Vision and Image Processing Fundamentals
Show steps
Establish a solid foundation by reviewing key concepts and techniques in computer vision and image processing, essential for understanding object detection algorithms.
Browse courses on
Computer Vision
Show steps
-
Review image representation and transformation techniques.
-
Explore image segmentation and feature extraction methods.
-
Study different approaches to object detection, including region-based and deep learning techniques.
Participate in Online Discussion Forums
Show steps
Foster collaboration and knowledge exchange by actively engaging in discussions with peers, sharing insights, and seeking clarification.
Browse courses on
Object Detection
Show steps
-
Identify relevant discussion forums or online communities.
-
Introduce yourself and share your interests in object detection.
-
Participate actively in discussions, asking thoughtful questions and providing informed answers.
-
Engage with other forum members, sharing resources and experiences.
Review 'TensorFlow for Developers'
Show steps
Review core concepts and techniques in TensorFlow, including object detection, to reinforce course materials and supplement practical labs.
View
Deep Learning with TensorFlow and Keras - Third...
on Amazon
Show steps
-
Identify key concepts and principles of TensorFlow.
-
Review the basics of object detection algorithms.
-
Follow along with code examples to implement an object detection model.
-
Experiment with different hyperparameters and datasets.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Complete Coursera's 'TensorFlow Object Detection Tutorial'
Show steps
Enhance understanding of object detection by completing interactive tutorials that provide step-by-step guidance.
Browse courses on
TensorFlow
Show steps
-
Set up your development environment and install TensorFlow.
-
Load and preprocess image data.
-
Build and train an object detection model.
-
Evaluate the model's performance.
Build and Deploy an Object Detection App
Show steps
Solidify knowledge by applying object detection concepts to a practical project, demonstrating proficiency and enhancing problem-solving skills.
Browse courses on
Object Detection
Show steps
-
Design the application's architecture and UI.
-
Integrate the object detection model into the app.
-
Develop user-friendly features for capturing and processing images.
-
Deploy the app to a cloud platform.
-
Test and refine the app's performance.
Practice Object Detection with Kaggle Competitions
Show steps
Sharpen object detection skills by participating in online competitions, gaining hands-on experience with real-world datasets and enhancing problem-solving abilities.
Browse courses on
Object Detection
Show steps
-
Identify relevant Kaggle competitions focused on object detection.
-
Study the competition rules and evaluation metrics.
-
Download and explore the provided datasets.
-
Develop and submit your own object detection models.
-
Analyze the results and compare your performance with others.
Create an Image Classification and Object Detection Portfolio
Show steps
Demonstrate comprehensive understanding and practical proficiency by building a portfolio of projects showcasing both image classification and object detection capabilities.
Browse courses on
Image Classification
Show steps
-
Gather a diverse set of images for both classification and detection tasks.
-
Develop models for image classification and object detection.
-
Train and evaluate the models on the collected datasets.
-
Create a visually appealing and informative portfolio website.
-
Present the portfolio to potential employers, clients, or the online community.
Assist Beginner Learners in Object Detection Projects
Show steps
Deepen understanding and solidify knowledge by mentoring others, providing guidance, support, and constructive feedback on their object detection projects.
Browse courses on
Mentoring
Show steps
-
Identify opportunities to mentor beginner learners.
-
Establish clear communication channels and set expectations.
-
Provide tailored guidance and support based on individual needs.
-
Review and provide feedback on project ideas, approaches, and code.
-
Encourage and motivate learners throughout their project journey.
Review Computer Vision and Image Processing Fundamentals
Show steps
Establish a solid foundation by reviewing key concepts and techniques in computer vision and image processing, essential for understanding object detection algorithms.
Browse courses on
Computer Vision
Show steps
Show steps
Show steps
- Review image representation and transformation techniques.
- Explore image segmentation and feature extraction methods.
- Study different approaches to object detection, including region-based and deep learning techniques.
Participate in Online Discussion Forums
Show steps
Foster collaboration and knowledge exchange by actively engaging in discussions with peers, sharing insights, and seeking clarification.
Browse courses on
Object Detection
Show steps
Show steps
Show steps
- Identify relevant discussion forums or online communities.
- Introduce yourself and share your interests in object detection.
- Participate actively in discussions, asking thoughtful questions and providing informed answers.
- Engage with other forum members, sharing resources and experiences.
Review 'TensorFlow for Developers'
Show steps
Review core concepts and techniques in TensorFlow, including object detection, to reinforce course materials and supplement practical labs.
View
Deep Learning with TensorFlow and Keras - Third...
on Amazon
Show steps
Show steps
Show steps
- Identify key concepts and principles of TensorFlow.
- Review the basics of object detection algorithms.
- Follow along with code examples to implement an object detection model.
- Experiment with different hyperparameters and datasets.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Complete Coursera's 'TensorFlow Object Detection Tutorial'
Show steps
Enhance understanding of object detection by completing interactive tutorials that provide step-by-step guidance.
Browse courses on
TensorFlow
Show steps
Show steps
Show steps
- Set up your development environment and install TensorFlow.
- Load and preprocess image data.
- Build and train an object detection model.
- Evaluate the model's performance.
Build and Deploy an Object Detection App
Show steps
Solidify knowledge by applying object detection concepts to a practical project, demonstrating proficiency and enhancing problem-solving skills.
Browse courses on
Object Detection
Show steps
Show steps
Show steps
- Design the application's architecture and UI.
- Integrate the object detection model into the app.
- Develop user-friendly features for capturing and processing images.
- Deploy the app to a cloud platform.
- Test and refine the app's performance.
Practice Object Detection with Kaggle Competitions
Show steps
Sharpen object detection skills by participating in online competitions, gaining hands-on experience with real-world datasets and enhancing problem-solving abilities.
Browse courses on
Object Detection
Show steps
Show steps
Show steps
- Identify relevant Kaggle competitions focused on object detection.
- Study the competition rules and evaluation metrics.
- Download and explore the provided datasets.
- Develop and submit your own object detection models.
- Analyze the results and compare your performance with others.
Create an Image Classification and Object Detection Portfolio
Show steps
Demonstrate comprehensive understanding and practical proficiency by building a portfolio of projects showcasing both image classification and object detection capabilities.
Browse courses on
Image Classification
Show steps
Show steps
Show steps
- Gather a diverse set of images for both classification and detection tasks.
- Develop models for image classification and object detection.
- Train and evaluate the models on the collected datasets.
- Create a visually appealing and informative portfolio website.
- Present the portfolio to potential employers, clients, or the online community.
Assist Beginner Learners in Object Detection Projects
Show steps
Deepen understanding and solidify knowledge by mentoring others, providing guidance, support, and constructive feedback on their object detection projects.
Browse courses on
Mentoring
Show steps
Show steps
Show steps
- Identify opportunities to mentor beginner learners.
- Establish clear communication channels and set expectations.
- Provide tailored guidance and support based on individual needs.
- Review and provide feedback on project ideas, approaches, and code.
- Encourage and motivate learners throughout their project journey.
Career center
Learners who complete Creating an Object Detection Application Using TensorFlow will develop knowledge and skills
that may be useful to these careers:
Computer Vision Engineer
Computer Vision Engineer
A Computer Vision Engineer designs, develops, and maintains computer vision systems. This course may be useful for Computer Vision Engineers who want to learn how to use TensorFlow to build object detection applications. The course can help Computer Vision Engineers gain the skills needed to develop and deploy object detection applications.
Deep Learning Engineer
Deep Learning Engineer
A Deep Learning Engineer designs, develops, and maintains deep learning models. This course may be useful for Deep Learning Engineers who want to learn how to use TensorFlow to build object detection applications. The course can help Deep Learning Engineers gain the skills needed to develop and deploy object detection applications.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and maintains machine learning models. This course may be useful for Machine Learning Engineers who want to learn how to use TensorFlow to build object detection applications. The course can help Machine Learning Engineers gain the skills needed to develop and deploy object detection applications.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
An Artificial Intelligence Engineer designs, develops, and maintains artificial intelligence systems. This course may be useful for Artificial Intelligence Engineers who want to learn how to use TensorFlow to build object detection applications. The course can help Artificial Intelligence Engineers gain the skills needed to develop and deploy object detection applications.
Robotics Engineer
Robotics Engineer
A Robotics Engineer designs, develops, and maintains robots. This course may be useful for Robotics Engineers who want to learn how to use TensorFlow to build object detection applications. The course can help Robotics Engineers gain the skills needed to develop and deploy object detection applications.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course may be useful for Software Engineers who want to learn how to use TensorFlow to build object detection applications. The course can help Software Engineers gain the skills needed to develop and deploy object detection applications.
Product Manager
Product Manager
A Product Manager is responsible for the development and launch of new products. This course may be useful for Product Managers who want to learn how to use TensorFlow to build object detection applications. The course can help Product Managers gain the skills needed to develop and launch object detection products.
Security Analyst
Security Analyst
A Security Analyst is responsible for identifying and mitigating security risks. This course may be useful for Security Analysts who want to learn how to use TensorFlow to build object detection applications. The course can help Security Analysts gain the skills needed to identify and mitigate security risks in object detection.
Research Scientist
Research Scientist
A Research Scientist conducts research in a variety of fields, including computer science, engineering, and medicine. This course may be useful for Research Scientists who want to learn how to use TensorFlow to build object detection applications. The course can help Research Scientists gain the skills needed to develop and deploy object detection applications.
Database Administrator
Database Administrator
A Database Administrator is responsible for managing and maintaining databases. This course may be useful for Database Administrators who want to learn how to use TensorFlow to build object detection applications. The course can help Database Administrators gain the skills needed to manage and maintain databases for object detection.
Data Scientist
Data Scientist
A Data Scientist uses data to solve business problems. This course may be useful for Data Scientists who want to learn how to use TensorFlow to build object detection applications. The course can help Data Scientists gain the skills needed to develop and deploy object detection applications.
Business Analyst
Business Analyst
A Business Analyst is responsible for analyzing business processes and identifying opportunities for improvement. This course may be useful for Business Analysts who want to learn how to use TensorFlow to build object detection applications. The course can help Business Analysts gain the skills needed to analyze business processes and identify opportunities for improvement in object detection.
Data Architect
Data Architect
A Data Architect is responsible for designing and managing data systems. This course may be useful for Data Architects who want to learn how to use TensorFlow to build object detection applications. The course can help Data Architects gain the skills needed to design and manage data systems for object detection.
Data Analyst
Data Analyst
A Data Analyst is responsible for collecting, analyzing, and interpreting data to identify trends and patterns. This course may be useful for Data Analysts who want to learn how to use TensorFlow and other machine learning libraries to build object detection applications. The course can help Data Analysts build a foundation in object detection and gain the skills needed to develop and deploy object detection applications.
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 learn how to use TensorFlow to build object detection applications. The course can help Project Managers gain the skills needed to plan, execute, and close object detection projects.
For more career information including salaries, visit:
OpenCourser.com/course/yydv3c/creating
Reading list
We've selected six 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
Creating an Object Detection Application Using TensorFlow.
Provides a comprehensive overview of deep learning for computer vision. It covers the different techniques used for deep learning, as well as the pros and cons of each technique.
Provides a comprehensive introduction to deep learning, including how to build and train neural networks.
Save
Provides a theoretical and practical introduction to machine learning for computer vision, including object detection.
Save
Provides a comprehensive overview of computer vision algorithms and applications, including object detection.
Provides a comprehensive overview of pattern recognition and machine learning, including object detection.
Save
This paper introduces the SSD object detection algorithm, which is known for its speed and accuracy.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/yydv3c/creating
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Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Good to know
Offers real-world practice through hands-on labs
Focuses on a highly relevant, in-demand skill
Taught by Google Cloud Training, a reputable organization in the tech industry
Suitable for beginners with little to no prior knowledge in object detection
Provides a foundation for further learning in computer vision and deep learning
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