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Machine Learning

Announcing Sisu's metric grain feature: Delivering faster, more accurate insights with ML

Organizations of every size have seen a massive increase in demand for faster, more comprehensive answers to vital business questions. Unfortunately, data’s increasing volume and dimensionality makes it difficult and time-consuming to analyze using business intelligence tools alone, often leaving rich and valuable data underutilized.

Shield Yourself Against Payment Frauds Using AI/ML Models

Scammers exist in all forms of commerce. With the advancement of e-commerce, fraud has taken on new forms and become more powerful than ever before. Fraudsters take full advantage of any loophole in any system. Preventing, detecting, and eliminating fraud is one of the major focus areas of the e-commerce and banking industries at present. Banks and other financial institutions are investing in new ways to meet the challenge of preventing fraud.

Using Snowpark As Part Of Your Machine Learning Workflow

Teams working on data science initiatives are tasked with deriving new insights from massive amounts of data. To accomplish this, teams work with compute environments that require heavy operational overhead, which means most of their time is spent extracting and processing features for machine learning model training and inference. Pairing Snowflake’s near-unlimited access to data and elastic processing engine with the most popular programming languages can change that, so more time can be spent on model development.