Amazon Deep Learning AMIs Reviews and Ratings

Use Cases and Deployment Scope

We use AWS EC2 for training machine learning models. For spinning up these instances, we use prebuilt AMIs specific for Deep Learning. These AMIs help a lot in setting up the environment very easily without any worries of installing CUDA, Nvidia Drivers, and then specific libraries like PyTorch, and Tensorflow. Support for various Conda environments is also available. The amazing part of this is that it provides support for different types of machines like Ubuntu, Linux, Amazon OS, etc.

Likelihood to Recommend

Suitable:

1. Best for quickly setting up an instance with pre-installed libraries.

2. Ideal for people in Deep Learning space who struggle with Cuda / Nvidia driver installations.

Not suitable:

1. People who want to install custom libraries or different version of those.

2. In these cases, updating the version of libraries many times leads to version mismatch which can cause many errors.

Use Cases and Deployment Scope

I work within a university setting within the school of computing where we use Amazon Deep Learning AMI as a cloud based alternative for deep learning in practical labs. Though we have high end hardware within our institution, not all students have access to this all of the time and as we have 100+ students on a Data Science/ Machine Learning Program this can cause issues with fair accessibility to equipment. This is where AMI comes into play, as we use this service to allow students to run complicated and intensive algorithms on significant data sets. This removes the need for expensive and inaccessible hardware in our lab spaces and gives our students the flexibility needed when learning about the intricacies of Deep Learning.

Likelihood to Recommend

Amazon AMIs has been very useful for the quick setup and implementation of deep learning for data analysis which is something I have used the service for in my own research. We commonly use the service to enable students to run intensive deep learning algorithms for their assessments. This service works well in this scenario as it allows students to quickly set up a suitable environment and get started with little hassle.

If you are looking to run simple, surface level deep learning algorithms (kind of contradictory statement I know) then AMI is more complicated than most will need. When it comes to teaching the basics of Machine Learning, this kind of system is unnecessary and there are other alternatives which can be used. That being said this service is a must if you are looking to run complex deep learning via the cloud.