Learn the approaches to enable AI project success
The big challenge for organizations looking to gain insights from advanced machine learning models is getting access to large volumes of clean and accurate data. Regardless of whether you build your own models or get them from third-parties, the work must be done to make sure that the data behind the models is of high quality.
To get the most out of advanced machine learning, companies need to focus on the complete data lifecycle. While this may not always be the most fun part of enterprise machine learning, the data lifecycle is incredibly important to get right. The data lifecycle starts well before any machine learning models can be built.
In this whitepaper, you will:
Learn the value of having access to clean data to train internal models.
Understand how to successfully manage the full data lifecycle
Discover tips to clean and prepare data for AI ingestion
