Without a well-defined strategy for collecting and structuring the data you need to train, test, and tune your AI systems, you run the risk of delayed projects, not being able to scale appropriately, and ultimately, competitors outpacing you.
Why Human-Annotated Data is Key to Machine Learning: Three Use Cases
Machine learning requires high volumes of data for training, validation, and testing. A machine learning model learns to find patterns in the input that is fed to it. This input is referred to as training data. As you train your solution to form relationships between variables, it’s important to have the right data, structured in the right format, covering all …
Insights from Chief Data Officer Summit 2018: Delivering a Superior Customer Experience with Data
Companies are looking for answers on how to integrate data to create a superior customer experience for their product.
