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Vinita Silaparasetty
Note: The rhyme platform currently does not support webcams, so this is not a live project.
This guided project is about optical character recognition using Pythorch, a Python library. This comes under the computer vision domain.
While you are watching...
Read more
Note: The rhyme platform currently does not support webcams, so this is not a live project.
This guided project is about optical character recognition using Pythorch, a Python library. This comes under the computer vision domain.
While you are watching...
Read more
Note: The rhyme platform currently does not support webcams, so this is not a live project.
This guided project is about optical character recognition using Pythorch, a Python library. This comes under the computer vision domain.
While you are watching me code, you will get a cloud desktop with all the required software pre-installed. This will allow you to code along with me. After all, we learn best with active, hands-on learning.
Note: This project 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/invedj/python
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Good to know
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what to watch for , and
possible dealbreakers
Develops OCR skills and knowledge using PyTorch, an industry-standard tool
Provides a hands-on project in a cloud desktop environment for active learning
Suitable for learners based in the North American region
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Reviews summary
Hands-on ocr with pytorch
Python Optical Character Recognition using Pytorch is a hands-on course that provides a full project focused on coding CNNs. This course uses Pytorch, a Python library for computer vision and machine learning. The course uses a cloud desktop to allow for live coding along with the instructor. There were some reoccurring problems, such as the code not working as expected, the instructor not running the cells in the notebook, and the lack of an accompanying completed project.
Excellent opportunity to learn through hands-on coding.
"This comes under the computer vision domain."
"While you are watching me code, you will get a cloud desktop with all the required software pre-installed."
"This will allow you to code along with me. After all, we learn best with active, hands-on learning."
Instructor's screen was cluttered and too many were open at the same time.
"We have explored a notebook (only left part visible on the screen) but don't run all the cells."
"There was an unnecessary left windows on screen !"
The course lacked a completed project to work with.
"The completed project isn't included, so instead of focusing on annotating the code - you first have to type it in"
The course did not provide guidance on how to apply the code to other image recognition problems.
"Lots of code. But it's unclear how to generalize it to other image recognition tasks."
The code given in the project did not work for many.
"The code is broken"
"waste of time, the code given doesn't even work"
"The code does not work"
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 Python Optical Character Recognition using Pytorch with these
activities:
Find a Mentor in Optical Character Recognition
Show steps
Finding a mentor can provide you with guidance and support as you learn about OCR.
Browse courses on
Optical Character Recognition
Show steps
-
Attend industry events and conferences
-
Reach out to professionals in your field
-
Search for online mentoring platforms
Optical Character Recognition Tutorial
Show steps
Following along with the guided project, you'll use PyTorch, a popular Python library for computer vision, to practice your OCR skills.
Browse courses on
Optical Character Recognition
Show steps
-
Watch the video tutorial
-
Code alongside the instructor
-
Complete the hands-on exercise
Optical Character Recognition Practice
Show steps
Practicing your OCR skills will help you improve your accuracy and efficiency in recognizing characters from images.
Browse courses on
Optical Character Recognition
Show steps
-
Find a dataset of OCR images
-
Write a script to load and process the images
-
Implement an OCR algorithm
-
Evaluate the performance of your algorithm
Two other activities
Expand to see all activities and additional details
Show all five activities
Optical Character Recognition Blog Post
Show steps
Creating a blog post about OCR will help you synthesize your learning and share your knowledge with others.
Browse courses on
Optical Character Recognition
Show steps
-
Choose a topic for your blog post
-
Research and gather information
-
Write your blog post
-
Publish your blog post
Optical Character Recognition Application
Show steps
Building an OCR application will allow you to apply your OCR skills to a real-world problem.
Browse courses on
Optical Character Recognition
Show steps
-
Define the scope of your project
-
Design the architecture of your application
-
Implement the OCR functionality
-
Test and debug your application
-
Deploy your application
Find a Mentor in Optical Character Recognition
Show steps
Finding a mentor can provide you with guidance and support as you learn about OCR.
Browse courses on
Optical Character Recognition
Show steps
Show steps
Show steps
- Attend industry events and conferences
- Reach out to professionals in your field
- Search for online mentoring platforms
Optical Character Recognition Tutorial
Show steps
Following along with the guided project, you'll use PyTorch, a popular Python library for computer vision, to practice your OCR skills.
Browse courses on
Optical Character Recognition
Show steps
Show steps
Show steps
- Watch the video tutorial
- Code alongside the instructor
- Complete the hands-on exercise
Optical Character Recognition Practice
Show steps
Practicing your OCR skills will help you improve your accuracy and efficiency in recognizing characters from images.
Browse courses on
Optical Character Recognition
Show steps
Show steps
Show steps
- Find a dataset of OCR images
- Write a script to load and process the images
- Implement an OCR algorithm
- Evaluate the performance of your algorithm
Two other activities
Expand to see all activities and additional details
Show all five activities
Optical Character Recognition Blog Post
Show steps
Creating a blog post about OCR will help you synthesize your learning and share your knowledge with others.
Browse courses on
Optical Character Recognition
Show steps
Show steps
Show steps
- Choose a topic for your blog post
- Research and gather information
- Write your blog post
- Publish your blog post
Optical Character Recognition Application
Show steps
Building an OCR application will allow you to apply your OCR skills to a real-world problem.
Browse courses on
Optical Character Recognition
Show steps
Show steps
Show steps
- Define the scope of your project
- Design the architecture of your application
- Implement the OCR functionality
- Test and debug your application
- Deploy your application
Career center
Learners who complete Python Optical Character Recognition using Pytorch will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and implement machine learning models. This course provides a solid foundation in the fundamentals of machine learning, including experience with Pytorch, a popular library for deep learning. With the increased demand for Machine Learning Engineers, this course will prepare you for a successful entry into this in-demand career field.
Software Engineer (Machine Learning)
Software Engineer (Machine Learning)
Software Engineers who specialize in Machine Learning are responsible for designing and developing software that uses machine learning algorithms. This course will help you build a solid foundation in machine learning with Python and Pytorch. By taking this course, you will be well-prepared for a career in this exciting and growing field.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers design and develop computer systems that can see and interpret images. This course can help you become familiar with the computer vision domain, which is a prerequisite for working as a Computer Vision Engineer. This course will also provide you with practical experience using Pytorch, which is a valuable tool for computer vision applications.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers design and develop artificial intelligence systems. This course will introduce you to the fundamental concepts of artificial intelligence and provide you with practical experience using Pytorch. With the increasing demand for Artificial Intelligence Engineers, this course will give you a competitive edge in the job market.
Software Developer - Machine Learning
Software Developer - Machine Learning
Software Developers who specialize in Machine Learning are responsible for designing and developing software that uses machine learning algorithms. This course will provide you with a practical understanding of the principles and techniques used by Software Developers who specialize in Machine Learning. The focus on Python and Pytorch will provide you with valuable skills for working with data in a variety of domains, including finance, healthcare, and retail.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve business problems. This course will provide you with a practical understanding of the principles and techniques used by Operations Research Analysts. The focus on Python and Pytorch will provide you with valuable skills for working with data in a variety of domains, including finance, healthcare, and retail.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. This course will provide you with a practical understanding of the principles and techniques used by Statisticians. The focus on Python and Pytorch will provide you with valuable skills for working with data in a variety of domains, including finance, healthcare, and retail.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze financial data. This course will provide you with a practical understanding of the principles and techniques used by Quantitative Analysts. The focus on Python and Pytorch will provide you with valuable skills for working with data in a variety of domains, including finance, healthcare, and retail.
Data Visualization Engineer
Data Visualization Engineer
Data Visualization Engineers design and develop data visualization systems. This course will provide you with a practical understanding of the principles and techniques used by Data Visualization Engineers. The focus on Python and Pytorch will provide you with valuable skills for working with data in a variety of domains, including finance, healthcare, and retail.
Data Scientist
Data Scientist
Data Scientists use data to solve problems and make better decisions. This course will provide you with a practical understanding of the principles and techniques used by Data Scientists. The focus on Python and Pytorch will provide you with valuable skills for working with data in a variety of domains, including finance, healthcare, and retail.
Data Analyst
Data Analyst
Data Analysts use their understanding of data to solve problems and make better decisions. Employers seek those with a strong understanding of data analysis principles and techniques. This course can help you develop proficiency with these principles and methods, which will enable you to access this field. The ability to use Python and Pytorch will make you a highly competitive candidate for a position in this growing sphere.
Big Data Engineer
Big Data Engineer
Big Data Engineers design and manage big data systems. This course may introduce you to some of the concepts and tools used by Big Data Engineers, such as Python and Pytorch. While this course will not fully prepare you for a career as a Big Data Engineer, it may be a helpful starting point.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to help businesses make better decisions. This course may provide you with some of the skills and knowledge needed to be a Business Intelligence Analyst, such as data analysis and visualization techniques. However, this course does not cover all of the topics that are typically required for a Business Intelligence Analyst position.
Cloud Architect
Cloud Architect
Cloud Architects design and manage cloud computing systems. This course is not directly related to cloud computing, but it may be useful for Cloud Architects who want to learn more about Python and Pytorch. Cloud Architects who are proficient in Python and Pytorch may be able to design and implement more efficient and effective cloud computing systems.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. This course is not directly related to product management, but it may be useful for Product Managers who want to learn more about Python and Pytorch. Product Managers who are proficient in Python and Pytorch may be able to better understand the technical aspects of product development.
For more career information including salaries, visit:
OpenCourser.com/course/invedj/python
Reading list
We've selected 11 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
Python Optical Character Recognition using Pytorch.
Save
Provides a comprehensive overview of deep learning techniques for image processing. It covers topics such as image classification, object detection, and image segmentation, which are fundamental to OCR systems.
Save
Offers an in-depth exploration of computer vision algorithms and their applications. It covers topics such as image formation, camera models, and image registration, which provide fundamental knowledge for understanding OCR systems.
Provides a comprehensive overview of deep learning concepts and techniques, including convolutional neural networks, recurrent neural networks, and generative adversarial networks. It valuable resource for understanding the technical foundations of OCR and computer vision systems.
Provides a comprehensive treatment of pattern recognition and machine learning techniques. It covers statistical methods, neural networks, and support vector machines, which are widely used in OCR systems for character recognition and classification.
Focuses specifically on deep learning techniques for computer vision tasks. It covers advanced topics such as object detection, image segmentation, and facial recognition, which are relevant to OCR systems.
Offers a comprehensive introduction to computer vision, covering topics such as image formation, image processing, and object recognition. It provides a solid foundation for understanding the principles behind OCR systems.
Classic in the field of pattern classification. It covers statistical and machine learning methods for classifying data, which are essential for understanding the techniques used in OCR systems for character recognition.
Covers the practical aspects of machine learning, including data preprocessing, model selection, and evaluation. It provides a solid understanding of the machine learning techniques used in OCR systems.
Offers a theoretical foundation of machine learning algorithms and their applications. It provides a deeper understanding of the principles behind OCR systems, such as statistical learning and optimization techniques.
Provides a foundational overview of artificial intelligence, including its history, principles, and applications. It helps learners understand the broader context of OCR and computer vision systems within the field of AI.
Provides an overview of artificial intelligence concepts, including natural language processing, computer vision, and machine learning. It offers a broad perspective on the field of AI and its applications.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/invedj/python
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Time
1 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Vinita Silaparasetty
Good to know
Develops OCR skills and knowledge using PyTorch, an industry-standard tool
Provides a hands-on project in a cloud desktop environment for active learning
Suitable for learners based in the North American region
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