Data Handling
Data handling refers to the processes involved in preparing and managing the data used for training, validating, and testing the model. Data handling includes several steps: first, data collection, where relevant information is gathered from various sources. Next, data cleaning removes any errors, duplicates, or irrelevant information to ensure the dataset is accurate. After that, data transformation is often necessary to convert the data into a format suitable for training, which might involve normalization or scaling.
This software is researched and edited by
Rajat Gupta is the founder of Spotsaas, where he reviews and compares software tools that help businesses work smarter. Over the past two years, he has analyzed thousands of products across CRM, HR, AI, and finance — combining real-world research with a strong foundation in commerce and the CFA program. He's especially curious about AI, automation, and the future of work tech. Outside of SpotSaaS, you'll find him on a badminton court or tracking the stock market.
Disclaimer: This research has been collated from a variety of authoritative sources. We welcome your feedback at [email protected].
