Amazon SageMaker Reviews

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Sandeep_Pandey
Real User
Data Scientist at a tech vendor with 10,001+ employees
Dec 22 2019

What is most valuable?

There are pre-built solutions for everything. For example, if you want to build a deep learning model, we already have AlexNet, the internet, and all of the packages are inside. You don't have to… more»

What needs improvement?

The pricing is complicated and should be simplified. I would suggest that Amazon SageMaker provide free slots to allow customers to practice, such as a free slot to try out working with a Sandbox… more»

What's my experience with pricing, setup cost, and licensing?

The pricing is complicated as it is based on what kind of machines you are using, the type of storage, and the kind of computation. It is already decided, but if you want to have a look at how it is… more»

Which solution did I use previously and why did I switch?

I researched Amazon SageMaker on my own.

What other advice do I have?

I am not exposed to Amazon SageMaker but I know it's capabilities. I know exactly what we can do and how we can do it. We have been provided with several solutions for image processing, speech… more»

Which other solutions did I evaluate?

We are not with Anaconda Solutions, we use their packages. We are exploring their interface and it's capabilities. We are currently on a different tool, on a different platform. We are using their… more»
PankajUrmaliya
Real User
Lead Data Scientist at a tech services company with 201-500 employees
Feb 04 2020

What is most valuable?

The deployment is very good, where you only need to press a few buttons. AWS CloudWatch, the monitoring system, is really good. You can write just a few rules to watch and see whether there are any changes in the deployment or the deployed models. The documentation is good.

What needs improvement?

The interface and the IDE are in need of improvement. For example, including drag and drop functionality would be helpful. If the ETL can be made a little better then that would be good for us. The entire machine learning project flow, or data science project flow, can be a little better. It is good… more»

Which solution did I use previously and why did I switch?

I have also used the Microsoft Azure Machine Learning Studio and Databricks, and the interface is a little better with these solutions. The Microsoft solution is really good in terms of user experience. When it comes to deployment and integrating with cloud services, Amazon SageMaker is better.

What other advice do I have?

My advice to anybody who is considering this solution is to think about using multiple cloud services. This solution is really good but it has a few problems. In terms of deployment, it is a clear winner. For developing machine learning models, taking the user experience into account, I would… more»
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ChrisDaly
Real User
Vice President & CIO with 51-200 employees
Sep 03 2019

What do you think of Amazon SageMaker?

What is our primary use case?

We use this solution for Outlier Detection using Random Cut Forest. We intend to implement a Predictive modeling project starting in October and have not yet decided on the platform(s) we will utilize. The challenge for us is balancing the Data Scientists, Technical vs. Analyst.

How has it helped my organization?

We are still learning the platform and will conduct more training as we evaluate it for other projects. The few projects we have done have been promising.

What is most valuable?

The most valuable features of this solution are the Random Cut Forest and the IDE.

What needs improvement?

I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time.

For how long have I used the solution?

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User Assessments By Topic About Amazon SageMaker

Find out what your peers are saying about Amazon, Databricks, Microsoft and others in Data Science Platforms. Updated: February 2020.
398,567 professionals have used our research since 2012.

Amazon SageMaker Questions

What is Amazon SageMaker?

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.

Also known as
AWS SageMaker, SageMaker
Amazon SageMaker customers

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit

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