Top Rated Amazon SageMaker Alternatives
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.
Video Reviews
Excellent service for ML end to end journey for small team
38 out of 39 Total Reviews for Amazon SageMaker
Overall Review Sentiment for Amazon SageMaker
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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 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.
Ability to implement AI ML capabilities and leverage existing ML models. Ability to integrate CI CD pipelines for MLOps. Review collected by and hosted on G2.com.
User Interface could be less cluttered and controlled, needs to be more web like. At the moment it looks and feels like a client tool hosted on web. CI CD can be more self managed. Review collected by and hosted on G2.com.
I like the endpoint creation which can inference our model through lambda function. Along with Sagemaker I used API gateway as well as to use the model in local environment. Review collected by and hosted on G2.com.
When I used sagemaker for object detection using py torch then it was not taking the image and I used to resize the image and then pass it to model. But in local it was working without even resizing the image Review collected by and hosted on G2.com.
SageMaker makes it very easy to train and deploy models. The managed infrastructure allows us to focus on business logic without needing to deal with things like cluster management, autoscaling, etc. Review collected by and hosted on G2.com.
Sometimes things can be a little overcomplicated to use. For example, the batch transform functionality requires us to write separate inference containers in addition to real-time inference containers. Review collected by and hosted on G2.com.
Sagemaker provides a platform for executing ML workflows well-integrated with other AWS services such as S3, Secrets Manager and Lambda etc. Review collected by and hosted on G2.com.
The Sagemaker Pipelines UI is less friendly than other pipeline orchestration tools such as Airflow and Azure. Sagemaker Studio and Image terminals are nowhere as nice as specialized IDEs such as IntelliJ for development purposes Review collected by and hosted on G2.com.
It's really helps in deploying applications faster and in a very convenient way. The pricing is also light on pocket. Review collected by and hosted on G2.com.
The thing I dislike about Amazon Sagemaker is, we need to remember some of the commands. Review collected by and hosted on G2.com.
In sagemaker we can have some of basic models and we can create complex AI models and train and test without hassle. Review collected by and hosted on G2.com.
Sagemaker is not having extensive data for images. Review collected by and hosted on G2.com.
Amazon SageMaker is widely present all over the world with remarkable technical support. Excellent knowledge and details of products and best tracking of shipments. Review collected by and hosted on G2.com.
Restrictions on destinations for certain products for reasons I do not know. But these warnings are informative to avoid losing money. Review collected by and hosted on G2.com.
