Compare Amazon Comprehend vs. Iguazio

Cancel
You must select at least 2 products to compare!
Amazon Comprehend Logo
229 views|213 comparisons
Iguazio Logo
4 views|0 comparisons
Ranking
28th
Views
229
Comparisons
213
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
35th
Views
4
Comparisons
0
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
Find out what your peers are saying about Alteryx, Databricks, Knime and others in Data Science Platforms. Updated: October 2020.
442,845 professionals have used our research since 2012.
Popular Comparisons
Learn
Amazon
Iguazio
Overview

Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. No machine learning experience required.

There is a treasure trove of potential sitting in your unstructured data. Customer emails, support tickets, product reviews, social media, even advertising copy represents insights into customer sentiment that can be put to work for your business. The question is how to get at it? As it turns out, Machine learning is particularly good at accurately identifying specific items of interest inside vast swathes of text (such as finding company names in analyst reports), and can learn the sentiment hidden inside language (identifying negative reviews, or positive customer interactions with customer service agents), at almost limitless scale.

Amazon Comprehend uses machine learning to help you uncover the insights and relationships in your unstructured data. The service identifies the language of the text; extracts key phrases, places, people, brands, or events; understands how positive or negative the text is; analyzes text using tokenization and parts of speech; and automatically organizes a collection of text files by topic. You can also use AutoML capabilities in Amazon Comprehend to build a custom set of entities or text classification models that are tailored uniquely to your organization’s needs.

For extracting complex medical information from unstructured text, you can use Amazon Comprehend Medical. The service can identify medical information, such as medical conditions, medications, dosages, strengths, and frequencies from a variety of sources like doctor’s notes, clinical trial reports, and patient health records. Amazon Comprehend Medical also identifies the relationship among the extracted medication and test, treatment and procedure information for easier analysis. For example, the service identifies a particular dosage, strength, and frequency related to a specific medication from unstructured clinical notes.

Amazon Comprehend is fully managed, so there are no servers to provision, and no machine learning models to build, train, or deploy. You pay only for what you use, and there are no minimum fees and no upfront commitments.

Data science is too important to today’s businesses to be held back by delays and inefficiencies. Iguazio was created to remove the obstacles preventing data science from seeing the light of day, helping teams seamlessly implement their creations into business applications and make game-changing impact on their industry.

Leaders

Offer
Learn more about Amazon Comprehend
Learn more about Iguazio
Sample Customers
LexisNexis, Vibes, FINRA, VidMob
Information Not Available
Find out what your peers are saying about Alteryx, Databricks, Knime and others in Data Science Platforms. Updated: October 2020.
442,845 professionals have used our research since 2012.
Amazon Comprehend is ranked 28th in Data Science Platforms while Iguazio is ranked 35th in Data Science Platforms. Amazon Comprehend is rated 0.0, while Iguazio is rated 0.0. On the other hand, Amazon Comprehend is most compared with Amazon SageMaker, Microsoft Azure Machine Learning Studio and IBM Watson Studio, whereas Iguazio is most compared with .

See our list of best Data Science Platforms vendors.

We monitor all Data Science Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.