A data science model is a statistical black box; testing it requires an understanding of mathematical techniques like algorithms, randomness, and statistics. To validate data science models you ...

Marketers need to build a testing model that can prove to stakeholders—and themselves—the true contribution of different data ...

Data scientists sometimes use synthetic data to train neural networks; at other times they use machine-generated data to validate a model’s results. Other synthetic data use cases are more specific: ...

The human impact of the inefficiency is considerable, and there is a strong desire for near-real-time and seamless flow of clinical data throughout the trial lifecycle, to unlock the full ...

Our understanding of progress in machine learning has been colored by flawed testing data. The 10 most cited AI data sets are riddled with label errors, according to a new study out of MIT, and it ...

Data quality testing platform Soda Data NV today announced the launch of SodaGPT, a data management platform that uses generative artificial intelligence to help users define data quality expectation ...

When analytics and experimentation converge, every behavior pattern becomes a hypothesis to test. Every test becomes a data point to analyze. Every decision becomes more grounded, targeted and ...