[First Tokyo WiMLDS Meeting]
by Tokyo Women in Machine Learning & Data Science
We are thrilled to announce the first event of Tokyo’s chapter of Women in Machine Learning and Data Science hosted and sponsored by Amazon Web Sevices Japan. All genders welcomed.
■ Venue Meguro Central Square ：3-1-1 Kamiosaki, Shinagawa-ku, Tokyo
■ Reception Meguro Central Square 17F
Title: Effective MLOps on AWS Cloud
Speaker: Shoko Utsunomiya. Machine Learning Solutions Architect at Amazon Web Services Japan.
In the operation of machine learning, there are various issues such as acquisition and annotation of high quality data, quick construction of training environment, preparation of elastic compute resources such as GPUs against demand fluctuation of calculation resource, and reduction of operation load of machine learning workflow.
Amazon Web Services (AWS) offers Amazon SageMaker, a fully managed machine learning platform service for solving these issues, and is used by customers of various sizes and stages. By removing Undifferentiated Heavy Lifting in a machine learning environment efficiently using managed services, you can focus on the more important differentiation issue, the data science tasks.
In this session, I will present the principles and best practices for machine learning in the cloud based on the past customer experiences. I will also introduce issues common to various use cases and their solutions, such as handling of large-scale data, transitioning research issues to actual operation, and launching of quick services.