Top things to know about Amazon Sagemaker
Amazon Sagemaker has multiple applications and use cases in our organization. It is used to create machine learning models for our call …
Overview
What is Amazon SageMaker?
Amazon SageMaker 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.
Recent Reviews
Product Details
- About
- Tech Details
What is Amazon SageMaker?
Amazon SageMaker 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 Technical Details
| Deployment Types | Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Unspecified |
| Mobile Application | No |
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Reviews and Ratings
(49)Reviews
(1-6 of 6)Companies can't remove reviews or game the system. Here's why
February 21, 2022
Top things to know about Amazon Sagemaker
- Machine Learning models help in reducing operating cost for manual intensive processes by deploying chatbots
- Improvement in product roadmap for learning about customer feedback on an early stage
- Supporting analytics and data science team to share correct insights and models with business teams
October 09, 2020
SageMaker : Good option for 'fail early learn fast' in ML and DL
- Using SageMaker, we can truly implement 'fail early, learn fast,' using an on-demand server for training.
- It also saves your money from investing in a physical server for very rare use.
- However, the pricing is high, but it will cost you only for what you use.
February 04, 2019
Amazon SageMaker is quite good at machine learning, as long as you're in the Amazon Ecosystem.
- SageMaker was a positive return on investment for those analysts that wanted to use new tools and had the aptitude to implement machine learning models with new resources. Such individuals were quick to improve their productivity with SageMaker.
- SageMaker was not a useful tool for analysts used to running reports on small data. Machine learning is a new area, and analysts that are only marginally interested in machine learning will find SageMaker not worth the effort.
- When used in combination with other machine learning tools, SageMaker is a perfect addition because it complements the Amazon ecosystem while the other tools provide more simple model development environments.
August 29, 2018
Incomplete but Promising
- We have been able to deliver data products more rapidly because we spend less time building data pipelines and model servers.
- We can prototype more rapidly because it is easy to configure notebooks to access AWS resources.
- For our use-cases, serving models is less expensive with SageMaker than bespoke servers.
May 21, 2018
AWS - The best!
- Easily integrates with our existing workflow
- Quick to get us results and reporting back.
- Database of algorithms and models already there for you to use.
March 29, 2018
Amazon SageMaker Review
- Use of this tool across areas of our organization has allowed for more time to be spent on other things as this is taking a lot of the heavy lifting and developing out of the machine learning process all together.
- Database of algorithms ready to use and adjust, customizing is key with this group of employees and their daily work while using this software.