The product can scale model training and deployment. It is one platform. It is easy to use. People who want to use the product must first focus on defining the workflow of their team without any tools and then see how the product adapts rather than trying to use all the features of the system. It can confuse us. Overall, I rate the solution a seven out of ten.

We are partners and resellers. Overall, I rate the product a nine out of ten.

Overall, I would rate the solution a nine out of ten. 

I use Amazon SageMaker in our production environment for making predictions in batches, ensuring efficient and scalable processing of large datasets.

Overall, I would rate Amazon SageMaker as a six out of ten.

Amazon SageMaker is definitely not the best product out there. I recommend that one can quickly do prototyping on SageMaker. It is easy to take your workload to the AWS Cloud. Amazon SageMaker's setup is very fast, so you'll be able to validate all your hypotheses pretty fast.

Overall, I rate the solution a seven out of ten.

Anyone doing on-prem at the moment for anything but their core datasets or legacy systems that can't be moved is just paying useless money.

I rate Amazon SageMaker a seven out of ten. I'd recommend it to other users. It's worth syncing the time and effort into getting it running.

I have not integrated Amazon SageMaker with other products in our company.

If someone plans to use the free trial version of Amazon SageMaker, then the person should be aware that it is chargeable since Amazon has not mentioned it in a written format. For enterprise-level users, there is nothing to worry about since their organization will take care of the costs attached to the solution.

I rate the overall tool an eight out of ten.

I am doing a benchmarking study between Databricks and Amazon SageMaker to determine the most cost-efficient and effective for our organization.

Amazon SageMaker is a pretty good solution for users who don't have any knowledge about their data and want to try different scenarios. The solution is fast and uses less code.

Overall, I rate Amazon SageMaker a seven out of ten.

From an exploration perspective, for people who cannot afford hardware at the physical location, it would be good to use the services from a cloud for leverage. It is easy to scale up or down when operating on an AWS Cloud. Suppose we have an on-premises or hybrid solution. In that case, we need to look at the economic structure of the organization, after which bringing everything into a physical location can get really complex. I suggest others explore using AWS before deciding on future plans.

I rate the overall solution a nine out of ten.

The solution works. It’s better than most of the other options available. We go through a long process to get the model in the hands of the users. SageMaker caters to all the processes involved with pre-built services. It makes the whole process very easy. Sometimes, the cost can be an issue, but it has all the right services we need. It is very smooth. Overall, I rate the solution a seven out of ten.

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.

I would give SageMaker a rating of six out of ten.

Myself and certain people in my team have just begun the training. There is an eight-hour training video to assist with learning how to use this solution.

I would rate this solution an eight out of ten.

I recommend the tool for document processing and would rate it an eight out of ten. 

I think for anyone using SageMaker it will help automate pipelines, and make it easier than doing the process manually. For anyone already on the AWS platform, they should definitely make use of it.

I would rate this product an eight out of 10. 

I rate Amazon SageMaker a seven out of ten.

My advice to anybody who is considering this solution is to think about using multiple cloud services. This solution is good but for complex business problems and big data, it gets a bit trickier. In terms of deployment, it is a clear winner.

From the cost point of view, it's relatively on the higher side.

Overall, there are a few improvements that I want but SageMaker is pretty good.

I would rate this solution a seven out of ten.