Amazon Tensor FLow
Pros
- Amazon Elastic Compute Cloud (EC2) allows resizable compute capacity in the cloud, providing the necessary elasticity to provide services for both, small and medium-sized businesses.
- Tensor Flow allows us to train our models much faster than in our on-premise equipment.
- Most of the pre-trained models are easy to adapt to our clients' needs.
Cons
- SageMaker isn't available in all regions. This is complicated for some clients overseas.
- For larger instances, when using a GPU, it takes a while to talk to a customer service representative to ask for a limit increase. Given this, it's recommendable to ask in advance for a limit increase in more expensive and larger cases; otherwise, SageMaker will set the limit to zero by default.
- Since the data has to be stored in S3 and copied to training, it doesn't allow to test and debug locally. Therefore, we have to wait a lot to check everything after every trail.
Return on Investment
- Positive: It has allowed us to work with our overseas teams without any large hardware investing.
- Positive: Pre-trained models significantly reduce the time to develop solutions for our clients.
- Negative: Since it's a relatively new tool, you have to be careful about not paying for large errors while learning to use the tool.
Alternatives Considered
Microsoft Azure Machine Learning Workbench, Google Cloud AI and Watson Studio (formerly IBM Data Science Experience)
Other Software Used
Microsoft Azure Machine Learning Workbench