We designed our system to fit the needs of data scientists and engineers, no matter which ML tasks they are tackling. Having said that, we’ve seen some use cases come up repeatedly within each industry.
With the advertising industry built around massive volumes of data, it has been one of the earliest adopters regarding machine learning. ML systems are used to simplify and automate audience segmentation, message personalization, and campaign management. They also enable dynamic creative optimization (adapting color, design, and layout for each viewer), predictive bidding, anomaly detection, detection of bots and ad fraud, and more. With a rapidly changing landscape and skills shortage, many companies face challenges when it comes to optimizing ad spend and maximizing returns. Continuously validating these data-driven systems, Deepchecks provides numerous alerts in real-time insights, enabling organizations to understand and adapt to market trends, detecting issues early on, and increasing ROAS (Return On Advertising Spend).