Tag: MLOps

Comet and Snowflake have partnered to offer data scientists faster and better model building solutions. The integration allows for effortless versioning and artifact tracking, enhanced MLOps capabilities, and simplified workflows, making it easy for data scientists to use Snowflake as their primary data source and understand how data changes affect model performance.

Deepchecks has launched its platform for public use, backed by $14 million seed funding led by Alpha Wave. Developed by CEO Philip Tannor and CTO Shir Chorev, the machine learning validation tool helps MLOps teams ensure high-quality models with continuous testing at every stage.

Make sure your machine learning models are safe and predictable with Deepchecks' open-source tool. Backed by $14M in seed funding, it offers comprehensive validation for optimal deployment and operation. Trusted by AWS, Booking.com, and Wix.

MLOps start-up Striveworks has secured $33m in its first round of funding. Its flagship Chariot platform enables teams to collaborate on machine learning models in low-code format. With partnerships with AWS and Azure, and a 300% annual ARR growth rate, Striveworks is poised for success.

Discover the benefits of using feature stores for businesses investing in machine learning. A central location for managing and serving features, allowing easy searching and accessing, reduces effort and enhances collaboration. Feature stores also increase accuracy and enable better governance and compliance. The article analyzes the three core components of data transformation, storage, and serving, ensuring faster and accurate machine learning models with compliance in governing the entire lifecycle of the process.