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Snehan Kekre
Welcome to this hands-on project on using Microsoft’s Custom Vision service for automated machine learning or AutoML as it’s popularly known. In this project, you are going to use Microsoft’s drag and drop tool to train your computer to recognize images of dogs and cats. We are going to do all of this without writing a single line of code! To take this guided-project, you do not need a background in computer science, machine learning or coding.
Read more
Welcome to this hands-on project on using Microsoft’s Custom Vision service for automated machine learning or AutoML as it’s popularly known. In this project, you are going to use Microsoft’s drag and drop tool to train your computer to recognize images of dogs and cats. We are going to do all of this without writing a single line of code! To take this guided-project, you do not need a background in computer science, machine learning or coding.
Read more
Welcome to this hands-on project on using Microsoft’s Custom Vision service for automated machine learning or AutoML as it’s popularly known. In this project, you are going to use Microsoft’s drag and drop tool to train your computer to recognize images of dogs and cats. We are going to do all of this without writing a single line of code! To take this guided-project, you do not need a background in computer science, machine learning or coding.
The only prerequisite for this project is that you have a Microsoft Azure account. If you don’t already have one, you will have to sign up for it.
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/jgijd2/automl
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What's inside
Syllabus
AutoML for Computer Vision with Microsoft Custom Vision
Welcome to this hands-on project on using Microsoft’s Custom Vision service for automated machine learning or AutoML as it’s popularly known. In this project, you are going to use Microsoft’s drag and drop tool to train your computer to recognize images of dogs and cats. We are going to do all of this without writing a single line of code! To take this guided-project, you do not need a background in computer science or machine learning or coding. The only prerequisite for this project is that you have a Microsoft Azure account. If you don’t already have one, you will have to sign up for it.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Suitable for beginners with no background in machine learning or computer science
Focuses on practical skills and eliminates the need for coding
Only applicable to learners located in North America at the moment
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Save AutoML for Computer Vision with Microsoft Custom Vision to your list so you can find it easily later:
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Reviews summary
Valuable introduction to custom vision
Learners say that this course is a great introduction to Microsoft Custom Vision. Many students report that the guided projects are very helpful in the learning process. This course is seen as useful for present industry technologies and is praised as a high-quality online course.
Course is useful for present industry technologies.
"useful for present technologies"
"I felt very happy for doing this project"
Guided projects are very helpful.
"the guided projects are very helpful in the learning process"
"guided projects"
Course is a great introduction to Microsoft Custom Vision.
"great introduction to custom vision"
"My first Guided project, it is very good we have a cloud interface side by side so that we can practice the tasks by pausing instructor video instruction and continue with you own pace. NO hassels to install software to setup development environment."
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 AutoML for Computer Vision with Microsoft Custom Vision with these
activities:
Read "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems"
Show steps
Gain a deeper understanding of machine learning concepts and techniques relevant to computer vision.
View
Hands-On Machine Learning with Scikit-Learn,...
on Amazon
Show steps
-
Read selected chapters or sections related to computer vision.
-
Work through the book's exercises and examples.
Follow guided tutorials on Microsoft Custom Vision
Show steps
Gain hands-on experience with Microsoft's Custom Vision platform.
Show steps
-
Find beginner-friendly tutorials on Microsoft Custom Vision.
-
Follow the tutorials step-by-step, building your own computer vision models.
-
Experiment with different settings and parameters.
Build a simple image classifier using Microsoft Custom Vision
Show steps
Apply your learning by creating a practical project that demonstrates your understanding of computer vision.
Show steps
-
Gather a dataset of images.
-
Train a custom vision model using Microsoft Custom Vision.
-
Evaluate the model's performance.
-
Deploy the model and test its accuracy.
Three other activities
Expand to see all activities and additional details
Show all six activities
Participate in online discussion forums or study groups
Show steps
Connect with peers to discuss course concepts, share knowledge, and get support.
Show steps
-
Join online discussion forums or study groups related to computer vision and AutoML.
-
Engage in discussions, ask questions, and share your insights.
Volunteer as a mentor or tutor for beginners in computer vision
Show steps
Reinforce your understanding by helping others learn and apply computer vision concepts.
Show steps
-
Identify opportunities to mentor or tutor beginners in computer vision.
-
Provide guidance, support, and resources to help them succeed.
Solve coding challenges related to computer vision
Show steps
Enhance your coding skills and problem-solving abilities in the context of computer vision.
Show steps
-
Find coding challenges or practice problems related to computer vision.
-
Attempt to solve the problems on your own.
-
Review solutions and learn from your mistakes.
Read "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems"
Show steps
Gain a deeper understanding of machine learning concepts and techniques relevant to computer vision.
View
Hands-On Machine Learning with Scikit-Learn,...
on Amazon
Show steps
Show steps
Show steps
- Read selected chapters or sections related to computer vision.
- Work through the book's exercises and examples.
Follow guided tutorials on Microsoft Custom Vision
Show steps
Gain hands-on experience with Microsoft's Custom Vision platform.
Show steps
Show steps
Show steps
- Find beginner-friendly tutorials on Microsoft Custom Vision.
- Follow the tutorials step-by-step, building your own computer vision models.
- Experiment with different settings and parameters.
Build a simple image classifier using Microsoft Custom Vision
Show steps
Apply your learning by creating a practical project that demonstrates your understanding of computer vision.
Show steps
Show steps
Show steps
- Gather a dataset of images.
- Train a custom vision model using Microsoft Custom Vision.
- Evaluate the model's performance.
- Deploy the model and test its accuracy.
Three other activities
Expand to see all activities and additional details
Show all six activities
Participate in online discussion forums or study groups
Show steps
Connect with peers to discuss course concepts, share knowledge, and get support.
Show steps
Show steps
Show steps
- Join online discussion forums or study groups related to computer vision and AutoML.
- Engage in discussions, ask questions, and share your insights.
Volunteer as a mentor or tutor for beginners in computer vision
Show steps
Reinforce your understanding by helping others learn and apply computer vision concepts.
Show steps
Show steps
Show steps
- Identify opportunities to mentor or tutor beginners in computer vision.
- Provide guidance, support, and resources to help them succeed.
Solve coding challenges related to computer vision
Show steps
Enhance your coding skills and problem-solving abilities in the context of computer vision.
Show steps
Show steps
Show steps
- Find coding challenges or practice problems related to computer vision.
- Attempt to solve the problems on your own.
- Review solutions and learn from your mistakes.
Career center
Learners who complete AutoML for Computer Vision with Microsoft Custom Vision will develop knowledge and skills
that may be useful to these careers:
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers design and develop systems that enable computers to interpret and understand images and videos. This course provides a great introduction to computer vision and automated machine learning, which are essential skills for Computer Vision Engineers.
Computer Vision Researcher
Computer Vision Researcher
Computer Vision Researchers focus on developing new methods and algorithms for computer vision systems. This course provides exposure to automated machine learning and its applications in computer vision, which is highly beneficial for Computer Vision Researchers.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build and maintain software systems that use machine learning to solve problems. This course provides hands-on experience with using automated machine learning, specifically within image recognition, which is highly valuable for Machine Learning Engineers working on computer vision projects.
Data Scientist
Data Scientist
Data Scientists design and apply statistical, machine learning, and data mining methods to solve real-world business problems. The course helps to build a foundation in automated machine learning, specifically within image recognition, which is a critical skill for Data Scientists working with image data.
Data Analyst
Data Analyst
Data Analysts analyze data to find patterns and trends. The course provides a good overview of automated machine learning, specifically within image recognition, which can be useful for Data Analysts working with image data.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. The course may be useful for Software Engineers who want to learn more about automated machine learning, specifically within image recognition, in order to develop more intelligent software systems.
Business Analyst
Business Analyst
Business Analysts analyze business processes and recommend ways to improve them. The course may be helpful for Business Analysts who need to understand how automated machine learning can be used to solve business problems, particularly in the area of image recognition.
Product Manager
Product Manager
Product Managers oversee the development and launch of new products. The course may be useful for Product Managers who need to understand how automated machine learning can be used to create new products or improve existing ones, particularly in the area of image recognition.
Marketing Manager
Marketing Manager
Marketing Managers develop and execute marketing campaigns. The course may be helpful for Marketing Managers who want to learn more about how automated machine learning can be used to improve marketing campaigns, particularly through the use of image recognition.
Sales Manager
Sales Manager
Sales Managers oversee sales teams and develop sales strategies. The course may be useful for Sales Managers who want to learn more about how automated machine learning can be used to improve sales performance, particularly through the use of image recognition.
Operations Manager
Operations Manager
Operations Managers oversee the day-to-day operations of a business. The course may be helpful for Operations Managers who want to learn more about how automated machine learning can be used to improve operational efficiency, particularly through the use of image recognition.
Project Manager
Project Manager
Project Managers plan and execute projects. The course may be useful for Project Managers who want to learn more about how automated machine learning can be used to improve project outcomes, particularly through the use of image recognition.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data and make investment recommendations. The course may be helpful for Financial Analysts who want to learn more about how automated machine learning can be used to improve financial analysis, particularly through the use of image recognition.
Human Resources Manager
Human Resources Manager
Human Resources Managers oversee the human resources department of a business. The course may be helpful for Human Resources Managers who want to learn more about how automated machine learning can be used to improve human resources processes, particularly through the use of image recognition.
Customer Success Manager
Customer Success Manager
Customer Success Managers help customers achieve success with a product or service. The course may be helpful for Customer Success Managers who want to learn more about how automated machine learning can be used to improve customer success, particularly through the use of image recognition.
For more career information including salaries, visit:
OpenCourser.com/course/jgijd2/automl
Reading list
We've selected eight 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
AutoML for Computer Vision with Microsoft Custom Vision.
Save
Provides a comprehensive overview of deep learning for computer vision, covering the latest techniques and applications. It valuable resource for anyone who wants to learn more about this field.
Save
Provides a comprehensive overview of computer vision algorithms and applications. It valuable resource for anyone who wants to learn more about this field.
Provides a comprehensive overview of machine learning for computer vision. It valuable resource for anyone who wants to learn more about this field.
Save
Provides a comprehensive overview of deep learning for image processing. It valuable resource for anyone who wants to learn more about this field.
Provides a comprehensive overview of computer vision. It valuable resource for anyone who wants to learn more about this field.
Provides a comprehensive overview of machine learning for computer vision, covering the foundations, theory, and applications. It valuable resource for anyone who wants to learn more about this field.
Save
Provides a comprehensive overview of computer vision principles and practice. It valuable resource for anyone who wants to learn more about this field.
Provides a comprehensive overview of machine learning for computer vision. It valuable resource for anyone who wants to learn more about this field.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/jgijd2/automl
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Effort
1.5 hours
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Snehan Kekre
Language
English
Good to know
Suitable for beginners with no background in machine learning or computer science
Focuses on practical skills and eliminates the need for coding
Only applicable to learners located in North America at the moment
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