Amazon SageMaker Reviews & Product Details

What I like best about Amazon SageMaker is its end-to-end support for the entire machine learning lifecycle. From data preparation and model building to training, tuning, and deployment, everything is seamlessly integrated into one platform. I especially appreciate the built-in algorithms, Jupyter notebooks, and automated model tuning (Hyperparameter Optimization). The ability to scale training jobs easily and deploy models as fully managed endpoints with a few clicks or lines of code is a huge productivity boost. SageMaker Studio also provides a great collaborative environment for teams. Review collected by and hosted on G2.com.

While Amazon SageMaker is powerful, one downside is its complexity and cost for beginners or small-scale projects. The learning curve can be steep, especially when configuring resources, managing permissions with IAM, or understanding the pricing model. Some features, like SageMaker Pipelines or Studio, can feel overwhelming without prior AWS experience. Additionally, debugging failed training jobs or deployments can be challenging without detailed logs or clear error messages. Review collected by and hosted on G2.com.

Amazon SageMaker supports the full machine learning workflow—from data preparation to model deployment—in one place.

We can easily load data, explore it, train models, and test them without switching tools.

I really like that SageMaker manages the servers for us, so we don’t have to set up or maintain any infrastructure.

It also makes deployment flexible and simple. Overall, it makes ML projects much easier to manage, especially when working in a team. Review collected by and hosted on G2.com.

It can be hard to learn at first, especially for beginners. The interface is sometimes slow or not very smooth, especially with large files or when switching tabs. Review collected by and hosted on G2.com.

End to end , Scalability and flexibility , Integration with AWS , ease of use , Model monitoring and debugging Review collected by and hosted on G2.com.

Cost management , challenging to customize or go beyond the pre-built functionalities , documentation clarity , A good understanding of ML and AWS is needed to fully utilize its capabilities Review collected by and hosted on G2.com.

What I like best about Amazon SageMaker is its ability to manage the entire machine learning lifecycle in one integrated platform. It simplifies model building, training, and deployment while offering scalability and powerful tools like SageMaker Studio and automated model tuning. Review collected by and hosted on G2.com.

What I dislike about Amazon SageMaker is that its pricing can be complex and quickly become expensive, especially for long-running training jobs or large-scale deployments. Additionally, the learning curve can be steep for new users unfamiliar with AWS services and configurations. Review collected by and hosted on G2.com.

Offers managed Jupyter notebooks (SageMaker Studio, Studio Lab), supports popular ML frameworks (TensorFlow, PyTorch, MXNet), and provides tools for distributed training and hyperparameter optimization. Review collected by and hosted on G2.com.

SageMaker is expensive, especially for long-running training jobs, large-scale deployments, or when using high-performance instances. The pay-as-you-go model can lead to unexpected costs, and the pricing structure can be complex to understand and optimize. Review collected by and hosted on G2.com.

No code & Infra headaches. Fully Managed e2e. Review collected by and hosted on G2.com.

Cost complications and pricing. Migration in other cloud is bit challenging. Review collected by and hosted on G2.com.

It is highly scalable, very compute-powerful, very well integrated with most vendors' data warehouses and data lakes, and can be accessed in the browser. Review collected by and hosted on G2.com.

I can hardly make an estimate of the price calculation. Even though there is some tool called AWS pricing calculator, the list of available configurations doesn't show the number of configurations you can select while setting up the tool Studio and Notebook instances. Review collected by and hosted on G2.com.

Provision of built in Algorithms and framework. Lot of the times, it's the data that causes the issues with the predictions. When we got the data right the predictions based on the built-in Algorithms did a great job in linear, logistic, classification techniques. Collaborative with other data scientists. It is easy to integrate with other related systems like Salesforce when we have our data in S3 buckets and the customer support is very responsive. Review collected by and hosted on G2.com.

Though we are getting compute for a reasonable costs, the onus of responsibility to run the large model lies witth the users. When they run larger models just to test it is attracting some additional costs. Though Sagemaker is easy to use, the cost management responsibility lies with the users. Review collected by and hosted on G2.com.

I am exclusively using Amazon SageMaker for both professional and personal usage. The variety of application make Handy while work upon machine learning task. The training and canvas features i've been using for quite some time there application make my ML task faster and productive Review collected by and hosted on G2.com.

Amazon SageMaker is great platform for Ml task all features and applications are really easy to use. The feature I need attention is the the offered free trial which are not sufficient and Amazon should provide gpu access also. Apart from this it's a great ml online platform Review collected by and hosted on G2.com.

i like how wonderfully it works based on numbers data or text data. i tried working on it along with other aws products like aws lamda and aws api gateway. and the documents or examples are also good for it Review collected by and hosted on G2.com.

i wanted to work on passing and image. or video input and get the image output out of it but was not really helpful as it takes the data in excel format and then we have to save it in s3 bucket. it retrives he data from it but not sure how to pass on in image in it. Review collected by and hosted on G2.com.