We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for these models, making accessing them convenient as needed.
Data specialist at a mining and metals company with 11-50 employees
Real User
Top 20
Jan 22, 2024
The Autopilot feature is really good because it's helpful for people who don't have much experience with coding or data pipelines. When we suggest SageMaker to clients, they don't have to go through all the steps manually. They can leverage Autopilot to choose variables, run experiments, and monitor costs. The results are also pretty accurate.
The tool has made client management easier where patients need to upload their health records and we can use the tool to understand details on treatment date, amount, etc.
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.
We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for these models, making accessing them convenient as needed.
The tool makes our ML model development a bit more efficient because everything is in one environment.
The Autopilot feature is really good because it's helpful for people who don't have much experience with coding or data pipelines. When we suggest SageMaker to clients, they don't have to go through all the steps manually. They can leverage Autopilot to choose variables, run experiments, and monitor costs. The results are also pretty accurate.
I have contacted the solution's technical support, and they were really good. I rate the technical support a ten out of ten.
The superb thing that SageMaker brings is that it wraps everything well. It's got the deployment, the whole framework.
Feature Store, CodeCommit, versioning, model control, and CI/CD pipelines are the most valuable features in Amazon SageMaker.
The solution's ability to improve work at my organization stems from the ensemble model and a combination of various models it provides.
The solution is easy to scale...The documentation and online community support have been sufficient for us so far.
The tool has made client management easier where patients need to upload their health records and we can use the tool to understand details on treatment date, amount, etc.
The most valuable feature of Amazon SageMaker is its integration. For example, AWS Lambda. Additionally, we can write Python code.
We've had no problems with SageMaker's stability.
Allows you to create API endpoints.
The most valuable feature of Amazon SageMaker is that you don't have to do any programming in order to perform some of your use cases.
The deployment is very good, where you only need to press a few buttons.
They are doing a good job of evolving.
The few projects we have done have been promising.