Add to Favourites
To login click here
This article discusses various strategies and techniques to optimize machine learning models for cost-effective cloud computing. Benefits of these strategies include selecting the right instance types based on workload and specific model requirements, optimizing resource allocation, and minimizing data transfer costs. These strategies are beneficial to data scientists and machine learning engineers who are looking to reduce the costs associated with running machine learning workloads on the cloud.
