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Amazon SageMaker OverviewUNIXBusinessApplication

Amazon SageMaker is #9 ranked solution in top Data Science Platforms. PeerSpot users give Amazon SageMaker an average rating of 8 out of 10. Amazon SageMaker is most commonly compared to Databricks: Amazon SageMaker vs Databricks. The top industry researching this solution are professionals from a computer software company, accounting for 24% of all views.
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.

Amazon SageMaker was previously known as AWS SageMaker, SageMaker.

Buyer's Guide

Download the Data Science Platforms Buyer's Guide including reviews and more. Updated: January 2022

Amazon SageMaker Customers

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

Amazon SageMaker Video

Archived Amazon SageMaker Reviews (more than two years old)

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Sandeep_Pandey
Data Scientist at a tech vendor with 10,001+ employees
Real User
A solution with great computational storage, has many pre-built models, is stable, and has good support
Pros and Cons
  • "They are doing a good job of evolving."
  • "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."

What is our primary use case?

I know about SageMaker and its capabilities, and what it can do, but I have not had any hands-on experience.

It's a machine learning platform for developers to create models.

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 recreate the same thing from scratch, but instead, you can use their models. You can use their model and use their data, then you can use your data.

I am a big fan of their computational storage capabilities. It's a relational database itself. It's a new SQL and you get different types of services. That is one of the best things that I like when doing my research.

I cannot quantify it as it is based on your requirements, but I can say that it's very flexible and you are able to increase all of the RAM and the GPU support.

They are doing a very good job on their end. They are evolving. I have learned that they have already integrated an IDE into Amazon SageMaker. They are doing a good job of evolving.

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. This would be beneficial for newcomers, especially those who are getting into the cloud space. They could explore this area and get all of the aspects including data engineering, data recognition, and data transformation.

For how long have I used the solution?

I have been familiar with this solution for three months.

What do I think about the stability of the solution?

From my findings, it's quite stable.

Amazon promises that they will provide you with stability, and it is quite a stable platform.

If you are facing any issues it may be related to the computational storage capability that you opted for. For example, if you are opting for a full code row and you have a lot of data that is taking a lot of time, then you have to go back to retrieve it. That flexibility is within the AWS, but you have to bear the cost.

What do I think about the scalability of the solution?

It's quite scalable.

How are customer service and technical support?

The technical support is very good and I am satisfied with it.

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

I researched Amazon SageMaker on my own.

How was the initial setup?

The initial setup is straightforward. It's not complex.

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 broken down or how they are calculating it, then they provide a tool where you can go and specify your options. These include what you want, how much storage, the RAM, and whether you want GPU support. You can include everything and then you can get the estimated cost.

AWS is an additional cost.

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 package managers to access the set of solutions deployed.

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 processing, and text processing. They have provided a built-in solution for every task. You can use tools for deploying your model, you just have to plug and play.

There is no cessation from what I can see. Whatever they have in the industry, they can solve 98% of the use cases.

There is also data engineering which is quite important. It's where the real work is done.

Amazon has already provided a free slot for each of the services that we have done. With Amazon SageMaker, however, I have not seen that.

I have not yet explored everything, but they are doing good work.

In terms of the dashboard, I can say that I have not explored the visualization aspect very much, but they have their tools. I don't know how flexible it is and how much customization you can do. That's something on the visualization side that I don't enjoy very much. My interests are mostly towards data engineering or data science.

I would rate this solution a nine out of ten.

Which deployment model are you using for this solution?

Public Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Vice President & CIO at a logistics company with 201-500 employees
Real User
Top 20
The Random Cut Forest Algorithm is helpful, but the IDE is immature and needs enhancing

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?

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?

We have been using this solution for six months.
Disclosure: I am a real user, and this review is based on my own experience and opinions.