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This talk starts with demos of the basic standard transforms using the albumentations Python package, and work up to some more advanced strategies like CutMix and mixup.
Read more
This talk starts with demos of the basic standard transforms using the albumentations Python package, and work up to some more advanced strategies like CutMix and mixup.
Read more
This talk starts with demos of the basic standard transforms using the albumentations Python package, and work up to some more advanced strategies like CutMix and mixup.
For machine learning models, we all know more data is better. For convolutional neural networks, image augmentation provides a straightforward way to expand your training dataset, by applying simple transformations to the images you already have. In this talk I'll start by demoing the basic standard transforms using the albumentations python package, and work up to some more advanced strategies like CutMix and mixup. I will also discuss some findings of the RxRx1 kaggle competition that Recursion ran last summer, and how this demonstrated the power of these techniques when applied to our cellular image data.
Register for this course and see more details by visiting:
OpenCourser.com/course/hcgp1w/image
What's inside
Syllabus
Image Augmentation: A Practical Guide to Prevent Overfitting in Computer Vision
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores basic and advanced image augmentation strategies widely used in computer vision
Provides hands-on demonstrations of the albumentations Python package
Highlights practical applications through use cases in the RxRx1 Kaggle competition
Assumes foundational knowledge in machine learning and computer vision
Save this course
Save Image Augmentation: A Practical Guide to Prevent Overfitting in Computer Vision to your list so you can find it easily later:
Save
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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 Image Augmentation: A Practical Guide to Prevent Overfitting in Computer Vision with these
activities:
Review Deep Learning with Python
Show steps
Reviewing this book will provide students with a deeper understanding of the theoretical foundations behind image augmentation.
View
Deep Learning with Python, Second Edition
on Amazon
Show steps
-
Read the introduction and chapter on image augmentation.
-
Work through the code examples in the book.
Review Convolutional Neural Networks (CNNs)
Show steps
Brushing up on CNNs will help students understand the core concepts of this course.
Browse courses on
Convolutional Neural Networks
Show steps
-
Read a blog post or article on CNNs.
-
Watch a tutorial video on CNNs.
-
Go through a hands-on example of CNN implementation.
Apply basic Albumentations transforms
Show steps
Hands-on practice with Albumentations will reinforce the techniques learned in the course.
Show steps
-
Install the Albumentations package.
-
Find a dataset of images.
-
Apply basic Albumentations transforms to the images.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Explore Advanced Albumentations Techniques
Show steps
Expanding knowledge of Albumentations with advanced techniques will enhance students' image augmentation skills.
Show steps
-
Find a tutorial on advanced Albumentations techniques.
-
Follow the tutorial and implement the techniques.
-
Apply the techniques to a dataset of images.
Augment a Dataset for a Computer Vision Project
Show steps
Creating a deliverable will provide students with practical experience in applying image augmentation techniques to real-world datasets.
Browse courses on
Computer Vision
Show steps
-
Identify a computer vision project to work on.
-
Collect a dataset of images for the project.
-
Apply Albumentations to augment the dataset.
Contribute to the Albumentations project
Show steps
Contributing to the Albumentations project will provide students with hands-on experience in the development and improvement of a valuable tool in the field of computer vision.
Browse courses on
Open Source
Show steps
-
Find an issue or feature request on the Albumentations GitHub repository.
-
Fork the Albumentations repository.
-
Make changes to the code to address the issue or implement the feature.
-
Submit a pull request to the Albumentations repository.
Participate in a Kaggle competition using Albumentations
Show steps
Participating in a Kaggle competition using Albumentations will challenge students to apply their skills in a real-world setting and push the boundaries of their knowledge.
Browse courses on
Kaggle
Show steps
-
Find a Kaggle competition that aligns with your interests and skills.
-
Download the competition data.
-
Preprocess the data using Albumentations.
-
Train and evaluate machine learning models.
-
Submit your results to the competition.
Review Deep Learning with Python
Show steps
Reviewing this book will provide students with a deeper understanding of the theoretical foundations behind image augmentation.
View
Deep Learning with Python, Second Edition
on Amazon
Show steps
Show steps
Show steps
- Read the introduction and chapter on image augmentation.
- Work through the code examples in the book.
Review Convolutional Neural Networks (CNNs)
Show steps
Brushing up on CNNs will help students understand the core concepts of this course.
Browse courses on
Convolutional Neural Networks
Show steps
Show steps
Show steps
- Read a blog post or article on CNNs.
- Watch a tutorial video on CNNs.
- Go through a hands-on example of CNN implementation.
Apply basic Albumentations transforms
Show steps
Hands-on practice with Albumentations will reinforce the techniques learned in the course.
Show steps
Show steps
Show steps
- Install the Albumentations package.
- Find a dataset of images.
- Apply basic Albumentations transforms to the images.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Explore Advanced Albumentations Techniques
Show steps
Expanding knowledge of Albumentations with advanced techniques will enhance students' image augmentation skills.
Show steps
Show steps
Show steps
- Find a tutorial on advanced Albumentations techniques.
- Follow the tutorial and implement the techniques.
- Apply the techniques to a dataset of images.
Augment a Dataset for a Computer Vision Project
Show steps
Creating a deliverable will provide students with practical experience in applying image augmentation techniques to real-world datasets.
Browse courses on
Computer Vision
Show steps
Show steps
Show steps
- Identify a computer vision project to work on.
- Collect a dataset of images for the project.
- Apply Albumentations to augment the dataset.
Contribute to the Albumentations project
Show steps
Contributing to the Albumentations project will provide students with hands-on experience in the development and improvement of a valuable tool in the field of computer vision.
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Find an issue or feature request on the Albumentations GitHub repository.
- Fork the Albumentations repository.
- Make changes to the code to address the issue or implement the feature.
- Submit a pull request to the Albumentations repository.
Participate in a Kaggle competition using Albumentations
Show steps
Participating in a Kaggle competition using Albumentations will challenge students to apply their skills in a real-world setting and push the boundaries of their knowledge.
Browse courses on
Kaggle
Show steps
Show steps
Show steps
- Find a Kaggle competition that aligns with your interests and skills.
- Download the competition data.
- Preprocess the data using Albumentations.
- Train and evaluate machine learning models.
- Submit your results to the competition.
Career center
Learners who complete Image Augmentation: A Practical Guide to Prevent Overfitting in Computer Vision will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data scientists use machine learning and other advanced analytical techniques to extract insights from data. They work in a variety of industries, including finance, healthcare, and retail. This course can help you develop the skills you need to become a data scientist. You will learn how to collect, clean, and analyze data, and how to use machine learning algorithms to build predictive models. This course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Machine Learning Engineer
Machine Learning Engineer
Machine learning engineers design, develop, and deploy machine learning models. They work in a variety of industries, including finance, healthcare, and manufacturing. This course can help you develop the skills you need to become a machine learning engineer. You will learn how to design, implement, and evaluate machine learning models. This course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Computer Vision Engineer
Computer Vision Engineer
Computer vision engineers develop and implement computer vision systems. They work in a variety of industries, including robotics, autonomous vehicles, and medical imaging. This course can help you develop the skills you need to become a computer vision engineer. You will learn how to design, implement, and evaluate computer vision systems. This course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Software Engineer
Software Engineer
Software engineers design, develop, and maintain software systems. They work in a variety of industries, including finance, healthcare, and manufacturing. This course can help you develop the skills you need to become a software engineer. You will learn how to design, implement, and test software systems. This course will also help you build a portfolio of projects that you can use to showcase your skills to potential employers.
Data Analyst
Data Analyst
Data analysts collect, clean, and analyze data to help businesses make informed decisions. They work in a variety of industries, including finance, healthcare, and retail. This course can help you develop the skills you need to become a data analyst. You will learn how to collect, clean, and analyze data, and how to use data visualization tools to communicate your findings.
Business Analyst
Business Analyst
Business analysts help businesses identify and solve problems. They work in a variety of industries, including finance, healthcare, and manufacturing. This course can help you develop the skills you need to become a business analyst. You will learn how to identify and solve problems, and how to communicate your findings to stakeholders.
Project Manager
Project Manager
Project managers plan, execute, and close projects. They work in a variety of industries, including construction, engineering, and software development. This course can help you develop the skills you need to become a project manager. You will learn how to plan, execute, and close projects, and how to manage teams and resources.
Product Manager
Product Manager
Product managers are responsible for the development and launch of new products. They work in a variety of industries, including technology, consumer goods, and manufacturing. This course can help you develop the skills you need to become a product manager. You will learn how to develop and launch new products, and how to manage product teams.
Marketing Manager
Marketing Manager
Marketing managers are responsible for developing and executing marketing campaigns. They work in a variety of industries, including consumer goods, retail, and technology. This course can help you develop the skills you need to become a marketing manager. You will learn how to develop and execute marketing campaigns, and how to manage marketing teams.
Sales Manager
Sales Manager
Sales managers are responsible for leading and motivating sales teams. They work in a variety of industries, including consumer goods, retail, and technology. This course may help you develop some of the skills you need to become a sales manager. You will learn how to lead and motivate teams, and how to develop and execute sales strategies.
Operations Manager
Operations Manager
Operations managers are responsible for the day-to-day operations of a business. They work in a variety of industries, including manufacturing, retail, and healthcare. This course may help you develop some of the skills you need to become an operations manager. You will learn how to manage teams, resources, and processes.
Financial Analyst
Financial Analyst
Financial analysts provide financial advice to individuals and businesses. They work in a variety of industries, including banking, investment management, and insurance. This course may help you develop some of the skills you need to become a financial analyst. You will learn how to analyze financial data and make investment recommendations.
Human Resources Manager
Human Resources Manager
Human resources managers are responsible for managing the human resources function of a business. They work in a variety of industries, including manufacturing, retail, and healthcare. This course may help you develop some of the skills you need to become a human resources manager. You will learn how to manage employee relations, compensation and benefits, and training and development.
Teacher
Teacher
Teachers educate students at all levels, from preschool to college. They work in a variety of settings, including public schools, private schools, and charter schools. This course may help you develop some of the skills you need to become a teacher. You will learn how to create lesson plans, manage classrooms, and assess student learning.
Librarian
Librarian
Librarians manage libraries and provide access to information. They work in a variety of settings, including public libraries, school libraries, and university libraries. This course may help you develop some of the skills you need to become a librarian. You will learn how to manage library collections, provide reference services, and conduct research.
For more career information including salaries, visit:
OpenCourser.com/course/hcgp1w/image
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
Image Augmentation: A Practical Guide to Prevent Overfitting in Computer Vision.
Provides a comprehensive overview of deep learning, including image augmentation techniques. It valuable resource for anyone who wants to learn more about deep learning and how to apply it to image augmentation.
Save
Provides a comprehensive overview of computer vision, including image augmentation techniques. It valuable resource for anyone who wants to learn more about computer vision and how to apply it to image augmentation.
Provides a comprehensive overview of deep learning for computer vision, including image augmentation techniques. It valuable resource for anyone who wants to learn more about deep learning for computer vision and how to apply it to image augmentation.
Save
Provides a comprehensive overview of deep learning with R, including image augmentation techniques. It valuable resource for anyone who wants to learn more about deep learning with R and how to apply it to image augmentation.
Provides a comprehensive overview of machine learning with R, including image augmentation techniques. It valuable resource for anyone who wants to learn more about machine learning with R and how to apply it to image augmentation.
Provides a comprehensive overview of machine learning with R, including image augmentation techniques. It valuable resource for anyone who wants to learn more about machine learning with R and how to apply it to image augmentation.
Provides a comprehensive overview of machine learning, including image augmentation techniques. It valuable resource for anyone who wants to learn more about machine learning and how to apply it to image augmentation.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/hcgp1w/image
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Time
28 hours
Level
Introductory
Via
Pluralsight
Instructor
Pluralsight LIVE
Language
English
Good to know
Explores basic and advanced image augmentation strategies widely used in computer vision
Provides hands-on demonstrations of the albumentations Python package
Highlights practical applications through use cases in the RxRx1 Kaggle competition
Assumes foundational knowledge in machine learning and computer vision
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