Nanonets Blog | AI Agents for Enterprise Data Processing (Page 27)

How to OCR Resumes using Intelligent Automation

Introduction Recruitment is a $200 Billion industry globally with millions of people uploading resumes and applying for jobs everyday on thousands of employment platforms. Businesses have their openings listed on these platforms and job seekers come apply. Every business has a dedicated recruitment

Understanding Bounding Boxes in Image Processing

Learn all the basics of bounding boxes in image processing. Train your machine learning models and scale new heights.

PYPDF2 Library: How Can You Work With PDF Files in Python?

The best library for working with PDFs in Python is PyPDF2. It’s lightweight, fast, and well-documented.

How to OCR Purchase Orders For Automation

This post outlines how to digitse Purchase Orders for Automation using Deep Learning. AI and ML can now be used to help in AP automation

What is a PDF Parser and how to parse data from PDFs?

A PDF parser or PDF parsing technology extracts data PDF documents to make them machine readable.

Deep Learning Based OCR for Text in the Wild

Learn how to apply deep learning based OCR to recognize and extract unstructured text information from images using Tesseract and the OpenCV EAST engine.

Table Detection, Table Extraction & Information Extraction using DL

Extract table from image with Nanonets table detection OCR. Learn OCR table Deep Learning methods to detect tables in images or PDF documents.

How to Parse Files in 2024 using OCR, Python, Java, Ruby and more

Learn to parse information from files. Explore OCR usage, programming languages, & automation. Discover real-world examples & workflows for efficient file parsing.