Amazon Tensor FLow
Rating: 9 out of 10
January 17, 2019
MQ
Vetted Review
Verified User
1 year of experience
We use Amazon Tensor Flow mainly for classification, regression, and clustering when using large databases and for overseas clients. The cloud capabilities allow us to smoothly provide a full service for our clients overseas
- 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.
- 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.
- Microsoft Azure Machine Learning Workbench, Google Cloud AI and Watson Studio (formerly IBM Data Science Experience)
Microsoft Azure is better than Amazon Tensor Flow because it provides easier and pre-built capabilities such as Anomaly Detection, Recommendation, and Ranking.
AWS is better than IBM Watson ML Studio because it has direct and prebuilt clustering capabilities
AWS, like IBM Watson ML Studio, has powerful built-in algorithms, providing a stronger platform when comparing it with MS Azure ML Services and Google ML Engine.
AWS is better than IBM Watson ML Studio because it has direct and prebuilt clustering capabilities
AWS, like IBM Watson ML Studio, has powerful built-in algorithms, providing a stronger platform when comparing it with MS Azure ML Services and Google ML Engine.