Item: Amazon Deep Learning AMIs
Rating: 8
Author: Verified User

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.

Pros and Cons

You can get several common packages including keras, pytorch and tensorflow setup within an environment ready to code on any AWS instance which saves time
Great for virtual applications that helps communicate between various pieces of software
Not need to worry about compatibility or any major aspects of setup e.g. GPU configuration

Some aspects of the User Interface are quite confusing and activating packages can be a bit convoluted
It can be a bit confusing to switch between frameworks for novice users

Return on Investment

It has made our Data Science/ Machine Learning Courses easier to manage/ need less human input therefore allowing us to increase the cohort size for this degree
It has unified a lot of technologies reducing the load on our IT team

Alternatives Considered

IBM Watson Machine Learning

Both of these services provide similar functionality and from my experience both are top class services which cover most of your needs. I think ultimately it comes down to what you need each service for. For example Amazon DL AMIs allows for clustering by default meaning I am able to run several clustering algorithms without a problem whereas IBM Watson Studio doesn't provide this functionality. They both provide a wide range of default packages such as Amazon providing caffe-2 and IBM providing sci-kitlearn. My main point is that both are very good services which have very similar functionality, you just need to think about the costs, suitability of features and integration with other services you are using.

Key Insights

Do you think Amazon Deep Learning AMIs delivers good value for the price?

Yes

Are you happy with Amazon Deep Learning AMIs's feature set?

Yes

Did Amazon Deep Learning AMIs live up to sales and marketing promises?

Yes

Did implementation of Amazon Deep Learning AMIs go as expected?

Yes

Would you buy Amazon Deep Learning AMIs again?

Yes

Other Software Used

IBM Watson Machine Learning, Azure AI (Cortana), Azure Lab Services

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.

Amazon Deep Learning - A nifty service for all your deep learning needs!

Overall Satisfaction with Amazon Deep Learning AMIs