eBook: 5 Steps to Train and Test Your AI Algorithm

AI adoption is rarely easy. With mountains of data and code to cover, it's hard to do alone. Here's a 5-step strategy to train and test the data for your AI algorithm.

Artificial intelligence and machine learning are taking us head-first into an increasingly digital world. AI/ML enables organizations to streamline processes, enabling them to move faster without relinquishing quality. However, successful algorithms require thorough training and testing data to produce reliable results and avoid bias.

The training and testing data will create the foundation for a successful AI algorithm and a reliable engine. This ebook reviews common challenges organizations face when training and testing your AI algorithm, and provides tips on how to avoid or manage them.

READ ON TO LEARN:

How to scale data for AI
Practices for testing bias
Tips for codifying data
How to get the most from your AI algorithm

LEADING COMPANIES UNDERSTAND DIGITAL EXPERIENCE

Applause is the worldwide leader in enabling digital quality. With the Product Excellence Platform, Applause provides a harmonized approach to quality that drastically improves testing coverage, reduces costs and speeds time-to-market for websites, mobile apps, IoT and in-store experiences.