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Amazon SageMaker

9 User Rating
10000+ No of Employees
1994 Founded
SaaS Industry
Artificial Intelligence Software Category
Andy Jassy CEO
Overview

Amazon SageMaker is a machine learning featured service by Amazon Web Services (AWS). The company began offering cloud computing services in 2006 and is now at the forefront of the web services industry. It boasts 175 featured services catering to a global clientele to businesses ranging from startups to huge brands that rely on their technology to optimize their operations.

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Pricing

Basic
$0.10/mo
$0.20/mo

Key Employees

ImageNameDesignationLinkedin
Frank BoosmanFrank BoosmanBusiness developerhttps://www.linkedin.com/in/fboosman
Don DrakeDon DrakeSr. Solutions Architecthttps://www.linkedin.com/in/don-drake-3631
John CombsJohn CombsBusiness Operationshttps://www.linkedin.com/in/johnmcombs

Reviews

“ User Friendly Product ”

9.5/10 (overall) - Nikita G
Pros
  • Provided an instance of Jupyter notebook for development script, which made it very easy to manage and develop any script.
  • Our system is cloud-based, and we are charged only for what we use and how long we use it.
Cons
  • It’s very good for the hardcore programmer, but a little bit complex for a data scientist or new hire who does not have a strong programming background.
  • Most of the popular library and ML frameworks are there, but we still have to depend on them for new releases.

“ Tool for taging every content ”

9/10 (overall) - Obaib E
Pros
  • We can choose multiple servers for Training, without any headache of distribution.
  • Most of the libraries are supported.
Cons
  • Amazon SageMaker is a great tool for a data scientist, although surprisingly, comparing different machine learning models with SageMaker is not as easy as one would think.
  • I think Amazon needs to team up with a data scientist who does ensemble modeling.

“ Easy to use ”

8/10 (overall) - Jenny U
Pros
  • SageMaker is good at serving models. The interface it provides is often clunky, but a managed, auto-scaling model server is powerful.
  • SageMaker is opinionated about versioning machine learning models and useful if you agree with its opinions.
Cons
  • SageMaker does not allow you to schedule training jobs.
  • SageMaker does not provide a mechanism for easily tracking metrics logged during training.

Features

  • Access Control
  • Analytics
  • API
  • Accounting Intergration
  • Agile Software Development
  • Assessment Management
  • Assignment Management
  • Business Intelligence
  • CRM Integration
  • Campaign Analysis
  • Campaign Management
  • Collaboration Tools
  • Collaborative Workspace
  • Customer Support
  • Customization

Images & Videos

Q & A

Q. How does Amazon SageMaker charge you?

Amazon SageMaker charges you according to what resources you use for notebook hosting, training predicting, and output logging, and how long you’re going to use it. The pricing also depends on your location. For instance, the Amazon SageMaker Studio notebooks are used with ml.t3.medium instances. Each hour for the mentioned instance costs $0.069 in the US West region. You’ll be billed for how long you’re going to utilize the resource along with other things you’re going to use.

Q. Do you need to pay for the Amazon SageMaker Studio?

No, you’re not going to pay for the Amazon SageMaker Studio. You’ll only be charged according to the services you use within the interface.

Q. What payment methods are available when using Amazon SageMaker?

AWS accepts major credit and debit cards, ACH direct debit (for qualified American customers), and SEPA direct debit (for qualified European customers.)