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The “Optical Character Recognition (OCR) MasterClass in Python” is a comprehensive training program designed to teach learners how to use Python for Optical Character Recognition (OCR) applications. OCR is the process of converting scanned images of text into machine-readable text. This course covers essential topics like image processing, feature extraction, and machine learning algorithms for OCR. Additionally, learners will gain hands-on experience with popular Python libraries like OpenCV, Tesseract, and PyTesseract.
The course also covers advanced topics like deep learning-based OCR and OCR using cloud services. By the end of the course, learners will have the knowledge and skills to build robust OCR applications using Python and be able to work with real-world datasets to solve complex problems. Whether you’re a beginner or an experienced Python developer, this masterclass is an excellent way to take your OCR skills to the next level.
Optical Character Recognition (OCR) MasterClass in Python Course Description
Welcome to Course “Optical Character Recognition (OCR) MasterClass in Python”
Optical character recognition (OCR) technology is a business solution for automating data extraction from printed or written text from a scanned document or image file and then converting the text into a machine-readable form to be used for data processing like editing or searching.
BENEFITS OF OCR:
- Reduce costs
- Accelerate workflows
- Automate document routing and content processing
- Centralize and secure data (no fires, break-ins or documents lost in the back vaults)
- Improve service by ensuring employees have the most up-to-date and accurate information
Some Key Learning Outcomes of this course are:
- Recognition of text from images using OpenCV and Pytesseract.
- Learn to work with Image data and manipulate it using Pillow Library in Python.
- Build Projects like License Plate Detection, Extracting Dates and other important information from images using the concepts discussed in this course.
- Learn how Machine Learning can be useful in certain OCR problems.
- This course covers basic fundamentals of Machine Learning required for getting accurate OCR results.
- Build Machine Learning models with text recognition accuracy of above 90%.
- You will learn about different image preprocessing techniques such as grayscaling, binarization, erosion, dilation etc… which will help to improve the image quality for better OCR results.
