Intelligently Extract Text & Data from Document with OCR NER
Intelligently Extract Text & Data from Document with OCR NER
Duration: 3h 8m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 1.14 GB
Genre: eLearning | Language: English
Duration: 3h 8m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 1.14 GB
Genre: eLearning | Language: English
Welcome to Course "Intelligently Extract Text & Data from Document with OCR NER" !!!
In this course you will learn how to develop customized Named Entity Recognizer. The main idea of this course is to extract entities from the scanned documents like invoice, Business Card, Shipping Bill, Bill of Lading documents etc. However, for the sake of data privacy we restricted our views to Business Card. But you can use the framework explained to all kinds of financial documents. Below given is the curriculum we are following to develop the project.
To develop this project we will use two main technologies in data science are,
Computer Vision
Natural Language Processing
In Computer Vision module, we will scan the document, identify the location of text and finally extract text from the image. Then in Natural language processing, we will extract the entitles from the text and do necessary text cleaning and parse the entities form the text.
Python Libraries used in Computer Vision Module.
OpenCV
Numpy
Pytesseract
Python Libraries used in Natural Language Processing
Spacy
Pandas
Regular Expression