Whitepapers & Insights
Insights and best practices for unraveling the complexities of digital data
Data Challenges in AI: User Perspectives and Insights
Discover findings on data needs, practices, and challenges from decision-makers and end-users of top AI companies.
The Latest Framework for Building Datasets & Driving AI Accuracy
Discover the principles of a data-centric approach to AI.
Zoning Documents for Data Extraction
Learn why zoning content within PDF’s and categorizing them into different zone types is an essential endeavor for creating training datasets.
The Art & Science of Data Annotation
Innodata and Société Generale’s Lourenco Miranda discuss how to prepare data for machine learning.
Accelerate AI with Data Annotation
Discover 9 best practices for creating effective training data from leading data-driven companies.
4 Steps to Build Truly Intelligent Machine Learning Models
Before investing time and money in machine learning, discover some of the key requirements needed to build an effective AI application.
5 Questions to Ask Before Getting Started with Data Annotation
Before you begin with any data annotation project, it's important to consider the following questions.
4 Critical Requirements for Building Truly Intelligent AI Models
Think you’re ready for AI? Make sure you have these 4 critical steps in order.
Data Annotation is the Fuel that Drives AI
Explore the 4 different types of data annotation modalities being used to create training data for machine learning.