Propel your ML use cases into production
Accelerate the training and development of ML models for 4 common machine learning use cases.
Making the right infrastructure decisions is essential to getting your ML models into production at scale and at optimal cost. But how can you really ensure that you have adequate infrastructure to support the compute, network, and storage needs of common ML use cases? Read Propel 4 Common Machine Learning Use Cases into Production for practical insights for setting-up your infrastructure for computer vision, fraud detection, natural language processing, and recommendations.