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Mining Data from Images
Justin Flett
Justin Flett
OpenCV is a widely-used data science and machine learning software library. This course will teach you the basics of Image Processing and Analysis using OpenCV with Python, including feature detection, image classification, and object detection.
Read more
OpenCV is a widely-used data science and machine learning software library. This course will teach you the basics of Image Processing and Analysis using OpenCV with Python, including feature detection, image classification, and object detection.
Read more
OpenCV is a widely-used data science and machine learning software library. This course will teach you the basics of Image Processing and Analysis using OpenCV with Python, including feature detection, image classification, and object detection.
Data Science and Machine Learning are rapidly growing fields that use scientific methods and processes to extract useful knowledge and insights from data. In this course, Mining Data from Images, you will learn foundational knowledge of solving real-world data science problems. First, you will learn the basics of implementing image processing problems including regions of interest and image similarity. Next, you will discover how feature detection can be implemented using OpenCV with Python. Finally, you will explore how to understand and implement more complex topics such as image classification and object detection. When you are finished with this course, you will have the skills and knowledge of image analysis and OpenCV needed to solve real-world data science and machine learning problems.
Register for this course and see more details by visiting:
OpenCourser.com/course/kwf0jw/mining
What's inside
Syllabus
Course Overview
Calculating Regions of Interest (ROI) in an Image
Calculating the Similarity Between Images
Identifying Common Features Found in an Image
Read more
Syllabus
Course Overview
Calculating Regions of Interest (ROI) in an Image
Calculating the Similarity Between Images
Identifying Common Features Found in an Image
Read more
Classifying Images into Categories
Detect and Identify Objects in an Image
Applying Style Transfer
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches image classification, which is standard in the data science field
Teaches object detection, which is commonly used in the AI field
Taught by Justin Flett, who is a well-known image data expert
Develops working knowledge of OpenCV, which is commonly used in image processing and analysis
Examines real-world applications of image analysis and machine learning, enhancing relevance and application
Requires working knowledge of Python, which may present a barrier for beginners without prior coding experience
Save this course
Save Mining Data from Images 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 Mining Data from Images with these
activities:
Brush up on your Python skills
Show steps
Refreshing your Python skills will help you to be more comfortable with the programming concepts used in OpenCV.
Browse courses on
Python
Show steps
-
Review your Python notes or take an online refresher course.
-
Complete some Python practice exercises.
Read 'Computer Vision with Python' by Jason Brownlee
Show steps
This book provides a comprehensive overview of computer vision, including image processing and analysis techniques and algorithms used by OpenCV.
View
Concurrent NumPy in Python: Faster NumPy With...
on Amazon
Show steps
-
Purchase or borrow a copy of the book.
-
Read the book and take notes.
-
Complete the practice exercises in the book.
Join an OpenCV study group
Show steps
Joining a study group will allow you to learn from and collaborate with other students who are also interested in OpenCV.
Browse courses on
OpenCV
Show steps
-
Find an OpenCV study group online or in your local area.
-
Join the study group and introduce yourself.
-
Participate in study group discussions and activities.
Ten other activities
Expand to see all activities and additional details
Show all 13 activities
Create a collection of image processing resources
Show steps
Creating a collection of resources will help you organize and easily access the information you need for your studies.
Browse courses on
Image Processing
Show steps
-
Identify the different types of resources you need, such as tutorials, articles, and code examples.
-
Find and collect resources from a variety of sources, such as online repositories and academic databases.
-
Organize your resources into a central location, such as a folder on your computer or a shared online document.
Follow OpenCV tutorials
Show steps
Following OpenCV tutorials will help you to understand and utilize OpenCV's powerful features for image processing and analysis.
Browse courses on
OpenCV
Show steps
-
Find OpenCV tutorials online.
-
Choose a tutorial that teaches something you want to learn.
-
Follow the tutorial step-by-step.
Organize course materials
Show steps
Organizing your notes, assignments, and other materials will help you stay on top of your coursework and make studying more efficient.
Show steps
-
Gather all of your course materials, including notes, assignments, and handouts.
-
Create a system for organizing your materials, such as using folders or a binder.
-
Regularly review your materials to stay up-to-date on the course content.
Practice image processing and analysis drills
Show steps
Practicing drills will help you develop proficiency in using OpenCV for image processing and analysis.
Browse courses on
Image Processing
Show steps
-
Download and install OpenCV on your computer.
-
Find online image processing and analysis drills.
-
Complete the drills regularly.
Follow tutorials on specific image processing techniques
Show steps
Following tutorials will provide you with step-by-step guidance on how to apply specific image processing techniques.
Browse courses on
Image Processing
Show steps
-
Identify a specific image processing technique that you want to learn more about.
-
Find a tutorial that covers the technique in detail.
-
Follow the steps in the tutorial to implement the technique.
Practice Identifying Features in Images
Show steps
Reinforce your understanding of feature detection by completing practice drills that help you identify features in images.
Browse courses on
Feature Detection
Show steps
-
Find a set of practice images online or in a textbook that includes images with identifiable features.
-
Examine each image and identify the key features.
-
Compare your findings with the provided answer key or with a peer.
Follow Tutorials on Object Detection
Show steps
Supplement your knowledge of object detection by following guided tutorials that provide step-by-step instructions on implementing object detection algorithms in OpenCV with Python.
Browse courses on
Object Detection
Show steps
-
Find online tutorials or video courses that teach object detection with OpenCV and Python.
-
Follow the instructions in the tutorials to implement object detection algorithms.
-
Practice using the algorithms on different images and datasets.
Build a simple image processing application
Show steps
Building a practical application will help you apply the concepts you learn in the course and deepen your understanding of image processing.
Browse courses on
Image Processing
Show steps
-
Choose a simple image processing task, such as resizing an image or applying a filter.
-
Design and implement an algorithm to perform the task.
-
Test and debug your application to ensure it works correctamente.
Develop a Case Study for Image Classification
Show steps
Enhance your understanding of image classification by creating a case study that applies the concepts learned in the course to a real-world scenario.
Browse courses on
Image Classification
Show steps
-
Identify a specific image classification problem that you want to solve.
-
Gather a dataset of images relevant to the problem.
-
Develop an image classification model using OpenCV with Python.
-
Evaluate the performance of your model and make necessary adjustments.
-
Write a report that outlines your methodology, results, and insights.
Create a tutorial or blog post on OpenCV
Show steps
Creating a tutorial or blog post on OpenCV will allow you to synthesize your knowledge and reinforce your understanding of the subject matter.
Browse courses on
OpenCV
Show steps
-
Choose a topic for your tutorial or blog post.
-
Write a draft of your tutorial or blog post.
-
Edit and proofread your tutorial or blog post.
-
Publish your tutorial or blog post online.
Brush up on your Python skills
Show steps
Refreshing your Python skills will help you to be more comfortable with the programming concepts used in OpenCV.
Browse courses on
Python
Show steps
Show steps
Show steps
- Review your Python notes or take an online refresher course.
- Complete some Python practice exercises.
Read 'Computer Vision with Python' by Jason Brownlee
Show steps
This book provides a comprehensive overview of computer vision, including image processing and analysis techniques and algorithms used by OpenCV.
View
Concurrent NumPy in Python: Faster NumPy With...
on Amazon
Show steps
Show steps
Show steps
- Purchase or borrow a copy of the book.
- Read the book and take notes.
- Complete the practice exercises in the book.
Join an OpenCV study group
Show steps
Joining a study group will allow you to learn from and collaborate with other students who are also interested in OpenCV.
Browse courses on
OpenCV
Show steps
Show steps
Show steps
- Find an OpenCV study group online or in your local area.
- Join the study group and introduce yourself.
- Participate in study group discussions and activities.
Ten other activities
Expand to see all activities and additional details
Show all 13 activities
Create a collection of image processing resources
Show steps
Creating a collection of resources will help you organize and easily access the information you need for your studies.
Browse courses on
Image Processing
Show steps
Show steps
Show steps
- Identify the different types of resources you need, such as tutorials, articles, and code examples.
- Find and collect resources from a variety of sources, such as online repositories and academic databases.
- Organize your resources into a central location, such as a folder on your computer or a shared online document.
Follow OpenCV tutorials
Show steps
Following OpenCV tutorials will help you to understand and utilize OpenCV's powerful features for image processing and analysis.
Browse courses on
OpenCV
Show steps
Show steps
Show steps
- Find OpenCV tutorials online.
- Choose a tutorial that teaches something you want to learn.
- Follow the tutorial step-by-step.
Organize course materials
Show steps
Organizing your notes, assignments, and other materials will help you stay on top of your coursework and make studying more efficient.
Show steps
Show steps
Show steps
- Gather all of your course materials, including notes, assignments, and handouts.
- Create a system for organizing your materials, such as using folders or a binder.
- Regularly review your materials to stay up-to-date on the course content.
Practice image processing and analysis drills
Show steps
Practicing drills will help you develop proficiency in using OpenCV for image processing and analysis.
Browse courses on
Image Processing
Show steps
Show steps
Show steps
- Download and install OpenCV on your computer.
- Find online image processing and analysis drills.
- Complete the drills regularly.
Follow tutorials on specific image processing techniques
Show steps
Following tutorials will provide you with step-by-step guidance on how to apply specific image processing techniques.
Browse courses on
Image Processing
Show steps
Show steps
Show steps
- Identify a specific image processing technique that you want to learn more about.
- Find a tutorial that covers the technique in detail.
- Follow the steps in the tutorial to implement the technique.
Practice Identifying Features in Images
Show steps
Reinforce your understanding of feature detection by completing practice drills that help you identify features in images.
Browse courses on
Feature Detection
Show steps
Show steps
Show steps
- Find a set of practice images online or in a textbook that includes images with identifiable features.
- Examine each image and identify the key features.
- Compare your findings with the provided answer key or with a peer.
Follow Tutorials on Object Detection
Show steps
Supplement your knowledge of object detection by following guided tutorials that provide step-by-step instructions on implementing object detection algorithms in OpenCV with Python.
Browse courses on
Object Detection
Show steps
Show steps
Show steps
- Find online tutorials or video courses that teach object detection with OpenCV and Python.
- Follow the instructions in the tutorials to implement object detection algorithms.
- Practice using the algorithms on different images and datasets.
Build a simple image processing application
Show steps
Building a practical application will help you apply the concepts you learn in the course and deepen your understanding of image processing.
Browse courses on
Image Processing
Show steps
Show steps
Show steps
- Choose a simple image processing task, such as resizing an image or applying a filter.
- Design and implement an algorithm to perform the task.
- Test and debug your application to ensure it works correctamente.
Develop a Case Study for Image Classification
Show steps
Enhance your understanding of image classification by creating a case study that applies the concepts learned in the course to a real-world scenario.
Browse courses on
Image Classification
Show steps
Show steps
Show steps
- Identify a specific image classification problem that you want to solve.
- Gather a dataset of images relevant to the problem.
- Develop an image classification model using OpenCV with Python.
- Evaluate the performance of your model and make necessary adjustments.
- Write a report that outlines your methodology, results, and insights.
Create a tutorial or blog post on OpenCV
Show steps
Creating a tutorial or blog post on OpenCV will allow you to synthesize your knowledge and reinforce your understanding of the subject matter.
Browse courses on
OpenCV
Show steps
Show steps
Show steps
- Choose a topic for your tutorial or blog post.
- Write a draft of your tutorial or blog post.
- Edit and proofread your tutorial or blog post.
- Publish your tutorial or blog post online.
Career center
Learners who complete Mining Data from Images will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist uses scientific methods and processes to extract knowledge and insights from data. In this role, you would leverage the skills you'll learn in this course to write code that cleans, analyzes, and visualizes data. You would also use statistical techniques to identify trends and patterns in data. This course provides a solid foundation for those seeking to start a career in Data Science.
Data Analyst
Data Analyst
A Data Analyst collects, analyzes, interprets, and presents data. In this role, you would use the skills you'll learn in this course to identify trends and patterns in data. You would also use statistical techniques to analyze data and draw conclusions. This course provides a strong foundation for those seeking to start a career in Data Analysis.
Computer Vision Engineer
Computer Vision Engineer
A Computer Vision Engineer designs, develops, and deploys computer vision systems. In this role, you would use the skills you'll learn in this course to build systems that can analyze images and videos. You would also use statistical techniques to evaluate the performance of computer vision systems. This course provides a strong foundation for those seeking to start a career in Computer Vision Engineering.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and deploys machine learning models. In this role, you would use the skills you'll learn in this course to build models that can learn from data and make predictions. You would also use statistical techniques to evaluate the performance of machine learning models. This course provides a strong foundation for those seeking to start a career in Machine Learning Engineering.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and deploys software applications. In this role, you would use the skills you'll learn in this course to write code that implements image processing algorithms. You would also use statistical techniques to evaluate the performance of software applications. This course provides a foundation for those seeking to start a career in Software Engineering.
Data Engineer
Data Engineer
A Data Engineer designs, builds, and maintains data pipelines. In this role, you would use the skills you'll learn in this course to write code that transforms and loads data into data warehouses. You would also use statistical techniques to monitor the performance of data pipelines. This course provides a foundation for those seeking to start a career in Data Engineering.
Financial Analyst
Financial Analyst
A Financial Analyst analyzes financial data and makes recommendations to investors. In this role, you would use the skills you'll learn in this course to build models that can predict the performance of financial assets. You would also use statistical techniques to evaluate the risk of financial investments. This course provides a foundation for those seeking to start a career in Financial Analysis.
Product Manager
Product Manager
A Product Manager plans and executes the development of new products. In this role, you would use the skills you'll learn in this course to analyze market data and identify new product opportunities. You would also use statistical techniques to evaluate the performance of new products. This course provides a foundation for those seeking to start a career in Product Management.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical models to analyze financial data. In this role, you would use the skills you'll learn in this course to build models that can predict the performance of financial assets. You would also use statistical techniques to evaluate the risk of financial investments. This course provides a foundation for those seeking to start a career in Quantitative Analysis.
Actuary
Actuary
An Actuary uses mathematical and statistical models to assess risk. In this role, you would use the skills you'll learn in this course to build models that can predict the likelihood of future events. You would also use statistical techniques to evaluate the risk of financial investments. This course provides a foundation for those seeking to start a career in Actuarial Science.
Business Analyst
Business Analyst
A Business Analyst analyzes business processes and makes recommendations for improvement. In this role, you would use the skills you'll learn in this course to design and conduct business analysis studies. You would also use statistical techniques to analyze data and draw conclusions. This course provides a foundation for those seeking to start a career in Business Analysis.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses mathematical and statistical models to solve business problems. In this role, you would use the skills you'll learn in this course to build models that can optimize business processes. You would also use statistical techniques to evaluate the performance of business processes. This course provides a foundation for those seeking to start a career in Operations Research.
Statistician
Statistician
A Statistician collects, analyzes, interprets, and presents data. In this role, you would use the skills you'll learn in this course to design and conduct statistical studies. You would also use statistical techniques to analyze data and draw conclusions. This course provides a foundation for those seeking to start a career in Statistics.
Market Researcher
Market Researcher
A Market Researcher collects, analyzes, and interprets data about consumers and markets. In this role, you would use the skills you'll learn in this course to design and conduct market research studies. You would also use statistical techniques to analyze data and draw conclusions. This course provides a foundation for those seeking to start a career in Market Research.
Technical Writer
Technical Writer
A Technical Writer creates documentation for technical products and services. In this role, you would use the skills you'll learn in this course to write clear and concise documentation for image processing and analysis software. You would also use statistical techniques to evaluate the effectiveness of your documentation. This course provides a foundation for those seeking to start a career in Technical Writing.
For more career information including salaries, visit:
OpenCourser.com/course/kwf0jw/mining
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
Mining Data from Images.
Provides a comprehensive introduction to OpenCV and discusses theoretical concepts as well as practical applications
Covers the theoretical foundations of computer vision and provides detailed explanations of various image processing and computer vision algorithms
This classic textbook provides a comprehensive overview of digital image processing, covering fundamental concepts, algorithms, and applications
Save
Covers advanced computer vision topics, including image segmentation, object detection, tracking, and recognition
Provides a comprehensive treatment of pattern classification, covering fundamental concepts, algorithms, and applications in image processing
Provides an in-depth understanding of computer vision, covering fundamental principles and advanced topics in image processing
Uses MATLAB to introduce digital image processing, providing a hands-on approach to image analysis and processing
For more information about how these books relate to this course, visit:
OpenCourser.com/course/kwf0jw/mining
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Time
99 hours
Level
Intermediate
Via
Pluralsight
Instructor
Justin Flett
Language
English
Good to know
Teaches image classification, which is standard in the data science field
Teaches object detection, which is commonly used in the AI field
Taught by Justin Flett, who is a well-known image data expert
Develops working knowledge of OpenCV, which is commonly used in image processing and analysis
Examines real-world applications of image analysis and machine learning, enhancing relevance and application
Requires working knowledge of Python, which may present a barrier for beginners without prior coding experience
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