Amazon Rekognition vs. IBM SPSS Modeler

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

Modeler is well suited for understanding consumer data. The ability to create a prediction and then to understand what is driving that prediction is strong in Modeler. Modeler is closely aligned with the CRISP-DM data mining approach meaning it is not just the 'doing' but also the theoretical background behind the development of data mining models.

Incentivized

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

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• A very nice and easy to use interface.
• A great variety of analytics, from statistical calculation to data validation and predictive statistics.
• Has a steep learning curve.

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• 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.

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• Some Analyses aren't there out of the box but can be added through open languages like R and Python.
• Graphs could be better.
• Unable to read data stored in OLAP databases

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.

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The ability to do predictive modeling, text analytics for both structured & unstructured data, decision management, optimization, and support for various data sources

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

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The online support board is helpful and the free add ons are incredibly appreciated.

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

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We additionally use SAS Data Miner as a toolkit. Compared to SAS Data Miner, the SPSS Modeler is a good competitor. SAS probably is more integrated in the market for a visual-based code for data science activities. However, I don't think it offers anything better than SPSS, and I really like several of the helpful components for usability for SPSS like peaks into nodes.

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• 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.

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• I am able to study and work from home sustainably
• I can help others have a high quality university education experience to graduate confident and competent to meet gaps in the wider community
• Market research for my business
• Help other small businesses to create viable and high quality products and services
• Contribute to research projects: ethical, high quality data analyses and interpretation

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