With this, the UiPath business automation platform helps data scientists, machine learning engineers, and business analysts easily automate building pipelines to reduce testing costs and accelerate innovation, the company said.
Amazon SageMaker is a managed service of Amazon Web Services that provides fully managed infrastructure, tools, and workflows for configuring data and building, training, and deploying machine learning models. Amazon SageMaker users can experience rapidly implementing new machine learning models in production, maximizing data science team productivity, and accelerating machine learning innovation by connecting to UiPath.
According to the company, new machine learning models can be quickly integrated into production workflows, reducing the time to business value creation. You can integrate SageMaker into your automation workflows without any additional coding, and manage your automation workflows and business processes end-to-end with UiPath Robot.
Consistent and accurate workflows can be configured to reduce labor input and free up key resources for mission-critical tasks. In particular, data science teams can take advantage of UiPath automation to reduce their workload by streamlining the process of deploying the latest machine learning models to end users. Additionally, governance and compliance can be further managed to improve reliability, for example by reducing human error, the company added.
Plus, engineering teams can speed up the process of testing ideas, solving problems, and experimenting with data. Automation minimizes manual tasks such as coding, troubleshooting code errors, and writing scripts throughout the machine learning data pipeline, and improves the speed and reliability of introducing new models machine learning in business processes.
“Tens of thousands of customers use Amazon SageMaker to train models with billions of parameters and generate trillions of predictions every month,” said Ankur Mehrotra, general manager of Amazon SageMaker at AWS. Through this, we will help customers reduce cost and time and build machine learning with an optimized infrastructure.
“As data scientists and data science team leaders develop powerful machine learning models that will accelerate business outcomes with the latest technologies, the cost and time spent on manual tasks is slowing development,” said said Graham Sheldon, Chief Product Officer, UiPath. SageMaker to the UiPath platform, we will be able to address this complexity, improve deployment speed and cost effectiveness, and unlock more innovation through machine learning.
editor@itworld.co.kr
