Amazon Deep Learning AMIs vs. Amazon Rekognition

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.

Incentivized

It is very well suited for image processing and recognition based applications and can be easily used using API calls without actually. writing any code for image processing. It can be used with any professional software development as it is built with so much precision. I would not suggest it for a sole feature-based application like image tagging only because for that you can create your own algorithm specific to a domain you want.

Incentivized

• Setting up environment
• Support for different types of machines
• Perfect for Machine Learning / Deep Learning use cases
• Nvidia / Cuda / Conda support easily

Incentivized

• Image tagging is very good.
• Object detection is precise.
• Video tagging has become very easy using Rekognition.

Incentivized

• 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

Incentivized

• The cost is bit more for small scale companies.
• For text processing, OCR is not available in amazon rekognition.
• Only facial search is available in image search.

Incentivized

Very much suitable for many applications where the image processing features are secondary and independent of any domain. This makes it a general solution and the recognition features are returned in a JSON object in response to the API called made which is a very simple process.

Incentivized

Support of Amazon is great. So far we are having a great experience using it.

Incentivized

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.

Incentivized

Accuracy and usability of amazon Rekognition are great. It provides many functionalities its competitors do not. Also, the Amazon service is great in general.

Incentivized

• 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

Incentivized

• The best thing it made our work fast.
• It reduces the chance of failure of a project which is based on image or video processing.
• We can assign anyone in our team to work on this as it very easy to use.

Incentivized