Amazon Comprehend vs. Amazon Forecast

Specifically, it starts processing millions of documents in minutes by leveraging the power of machine learning without having trained models from scratch. If any of the content contains personally identifiable information not only can Amazon Comprehend locate it but it will also redact or mask it. Using NLP techniques Amazon Comprehend goes well beyond keyword search or rules-based tagging to accurately classify documents. For my task or development, I cannot find any difficulties with Amazon Comprehend.

Incentivized

I personally get the feeling that Amazon Forecast must have been a direct product released on the models Amazon themselves must have used at some port. Amazon Forecast definitely shines when using it for product demand, inventory, and pricing throughout store locations, etc. Everything, including data-set importing, works best in this context. When applying it to more edge cases like resource planning around events, it can be a bit more tricky to apply effectively.

Incentivized

• Amazon Comprehend identifies the language of the text and extracts Key-phrases, places, people, brands or events.
• It can build a custom set of entities or text classification models that are tailored uniquely to the organisation's need
• Amazon Comprehend's medical can be used to identify medical conditions, medications, dosages, strength and frequencies from sources like doctor's notes, clinical trial reports and patient health records. This service is very good and with well an accuracy or confidence score.

Incentivized

• Develop benchmarks for use in future forecast.
• Performs contingency planning during challenging financial times.
• Anticipate the impact of new expanse.

Incentivized

• It will be great if Amazon Comprehend provide support specifically for litigation or related text documents to extract insights from it.
• For REST API support using JAVA SDK, it will be great for developers if they provide support for testing without any credentials or account details.
• Setting up for REST API integration can be as simple as possible.

Incentivized

• Potential very high costs
• Predicting ongoing running costs
• Very product focused

Incentivized

For natural language processing tasks or techniques, there are many service providers out there in the market such as Azure Cloud Services, IBM Watson and Google Cloud Platform (GCP), but compared with them, Amazon Comprehend is the best service provider in contents of accuracy, speed of processing multilingual text, supporting SDK for most of the languages and well documented.

Incentivized

There was no other product or service that was considered before making the choice to go with Amazon Forecast as the forecasting that the company was looking for had everything running in the AWS environment, the choice had to be obvious. Integrating with Amazon Forecast also ensured that everything is under a single roof and we didn't have to go multiple places looking for data when needed.

Incentivized

• It supports better and accurately as compared with our existing or old implementations. So, we fulfil our needs as per clients' requirements and it will help to grow or improve client satisfaction.
• For these specific requirements, we do not require any machine learning engineers or related professionals to hire in our organisation.
• None of any negative sides can be affected our business or distract existing clients.

Incentivized

• Insights have been available much more quickly and well designed manner
• Integration with other tools has been flawless

Incentivized