Optimize your ML inference price performance using SageMaker Inference Recommender (Hebrew)

Selecting a compute instance with the best price performance for deploying machine learning (ML) models is a complicated, iterative process that can take weeks of experimentation. Amazon SageMaker Inference Recommender reduces the time required to deploy ML models from weeks to hours by automatically selecting the right compute instance type, instance count, container parameters, and model optimizations for inference to maximize performance and minimize cost. You can then deploy your model to one of the recommended instances or run a fully managed load test on a set of instance types you choose without worrying about testing infrastructure. Join us to see how this works. Subscribe to AWS Online Tech Talks On AWS: https://www.youtube.com/@AWSOnlineTechTalks?sub_confirmation=1 Follow Amazon Web Services: Official Website: https://aws.amazon.com/what-is-aws Twitch: https://twitch.tv/aws Twitter: https://twitter.com/awsdevelopers Facebook: https://facebook.com/amazonwebservices Instagram: https://instagram.com/amazonwebservices ☁️ AWS Online Tech Talks cover a wide range of topics and expertise levels through technical deep dives, demos, customer examples, and live Q&A with AWS experts. Builders can choose from bite-sized 15-minute sessions, insightful fireside chats, immersive virtual workshops, interactive office hours, or watch on-demand tech talks at your own pace. Join us to fuel your learning journey with AWS. #AWS