Question 1

这些数据的来源是什么?

Accepted Answer

我们的数据来自于从数百万家公司收集的招聘信息。我们在公司网站、招聘平台和其他招聘平台上监控这些招聘信息。分析招聘信息提供了一种可靠的方法来了解公司正在使用的技术，包括他们使用的内部工具。

Question 2

数据多久更新一次?

Accepted Answer

我们每天更新数据，以确保您访问的是最新的可用信息。这一频繁的更新过程保证了我们的洞察力和情报反映了行业内的最新发展和趋势。

Question 3

什么是Amazon Comprehend?

Accepted Answer

Amazon Comprehend is a powerful natural language processing NLP service provided by Amazon Web Services AWS It offers a range of tools and functionalities to analyze text data extract insights and understand sentiment making it a valuable asset for companies looking to derive valuable information from textual content Amazon Comprehend utilizes machine learning algorithms to perform tasks such as entity recognition key phrase extraction language detection sentiment analysis and topic modeling

In the category of NLPSentiment Analysis Amazon Comprehend stands out as a comprehensive solution for businesses seeking to make sense of unstructured text data By offering a wide array of NLP capabilities it enables organizations to gain deeper understanding of customer feedback enhance content categorization and improve overall decisionmaking processes Amazon Comprehend can be seamlessly integrated into various applications and workflows making it a versatile tool for a wide range of industries

Founded in 2017 Amazon Comprehend was introduced by Amazon Web Services as part of its suite of AI and machine learning services The motivation behind the development of Amazon Comprehend was to democratize access to advanced NLP capabilities enabling businesses of all sizes to leverage the power of natural language processing without the need for inhouse expertise Since its inception Amazon Comprehend has continued to evolve and enhance its features solidifying its position as a leading NLP service in the market

Currently Amazon Comprehend holds a significant market share within the NLPSentiment Analysis category driven by its robust capabilities seamless integration with other AWS services and a strong track record of delivering accurate insights With the increasing demand for NLP solutions in industries such as customer service marketing and content analysis it is anticipated that Amazon Comprehend will continue to experience growth in the future As businesses strive to gain deeper insights from text data and improve customer experiences the demand for advanced NLP tools like Amazon Comprehend is expected to remain strong

Question 4

如何获得使用Amazon Comprehend的公司的最新列表？

Accepted Answer

您可以访问 TheirStack.com，获取使用 Amazon Comprehend 的公司更新名单。我们的平台提供了一个全面的数据库，涵盖了使用各种技术和内部工具的公司。

Question 5

Amazon Comprehend 有多少客户？

Accepted Answer

截至目前，我们拥有关于 380 家使用 Amazon Comprehend 的公司的数据。

Question 6

谁在使用Amazon Comprehend?

Accepted Answer

Amazon Comprehend 被广泛应用于包括 "It Services And It Consulting", "Telecommunications", "E-Learning Providers", "Outsourcing And Offshoring Consulting", "Software Development", "It Services And It Consulting", "It Services And It Consulting", "Real Estate" 在内的各个行业的各种组织中。欲了解所有使用 Amazon Comprehend 的行业的完整列表，请访问 TheirStack.com。

Question 7

哪些公司使用Amazon Comprehend?

Accepted Answer

一些使用Amazon Comprehend的公司包括InterVision Systems, USAN, LifeWeb 360, FPS - Full Potential Solutions, Neoboard, Full Potential Solutions, JupiterOne, Amazon Web Services, Inc., APPIC Solutions LLC, CoStar Group以及更多公司。您可以在TheirStack.com上找到使用Amazon Comprehend的380家公司完整列表。

Question 8

哪些国家使用Amazon Comprehend最多？

Accepted Answer

根据我们的数据，Amazon Comprehend 在 美国 (182 companies), 英国 (20 companies), 澳大利亚 (8 companies), 加拿大 (8 companies), 印度 (8 companies), 法国 (6 companies), 西班牙 (4 companies), 瑞士 (4 companies), 爱尔兰 (2 companies), 荷兰 (2 companies) 最受欢迎。然而，它被全世界的公司所使用。

Question 9

如何找到使用Amazon Comprehend的公司？

Accepted Answer

您可以在TheirStack.com上搜索Amazon Comprehend，来找到使用该技术的公司。我们跟踪数百万家公司的招聘信息，并借此发现他们正在使用的技术和内部工具。

Company	Country	Industry	Employees	Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue
Company name Industry Size Revenue

公司	国家	行业	雇员	收入	技术
InterVision Systems	美国	It Services And It Consulting	550	$38M	Amazon Comprehend
USAN	美国	Telecommunications	220	$35M	Amazon Comprehend
LifeWeb 360					Amazon Comprehend
FPS - Full Potential Solutions					Amazon Comprehend
Neoboard	美国	E-Learning Providers			Amazon Comprehend
Full Potential Solutions	美国	Outsourcing And Offshoring Consulting	810	$2.4M	Amazon Comprehend
JupiterOne	美国	Software Development	180	$4.9M	Amazon Comprehend
Amazon Web Services, Inc.	美国	It Services And It Consulting	1.5M	$3M	Amazon Comprehend
APPIC Solutions LLC	美国	It Services And It Consulting	20		Amazon Comprehend
CoStar Group	美国	Real Estate	6.1K	$2.3B	Amazon Comprehend

使用 Amazon Comprehend 的公司

如何针对Amazon Comprehend用户进行定位

使用 Amazon Comprehend 的公司

如何针对Amazon Comprehend用户进行定位

这些数据的来源是什么?

这些数据的来源是什么?

数据多久更新一次?

数据多久更新一次?

什么是Amazon Comprehend?

什么是Amazon Comprehend?

如何获得使用Amazon Comprehend的公司的最新列表？

如何获得使用Amazon Comprehend的公司的最新列表？

Amazon Comprehend 有多少客户？

Amazon Comprehend 有多少客户？

谁在使用Amazon Comprehend?

谁在使用Amazon Comprehend?

哪些公司使用Amazon Comprehend?

哪些公司使用Amazon Comprehend?

哪些国家使用Amazon Comprehend最多？

哪些国家使用Amazon Comprehend最多？

如何找到使用Amazon Comprehend的公司？

如何找到使用Amazon Comprehend的公司？

使用Amazon Comprehend的公司所在国家

美国

英国

澳大利亚

加拿大

印度

法国

西班牙

瑞士

爱尔兰

荷兰

使用Amazon Comprehend的公司列表

Amazon Comprehend 替代品和竞争对手

TensorFlow

PyTorch

Bard AI

scikit-learn

Microsoft LUIS

ENorm

ML Flow

Neuro

CUDA

MLflow

Lateral

Stan

Azure Machine Learning

Amazon SageMaker

Kubeflow

Amazon Machine Learning

NLTK

Caffe

Streamlit

Propel

Appen

Trax

IBM Watson

Amazon Text to Speech

Apache MXNet

MXNet

Ludwig

Aquarium

Fritz

Kur

Lamina

Clipper

Renate

Igel

Weka

Apache Spark MLlib

Document AI

Google AI Platform

Manifold

Amazon Textract

Tensorflow Lite

Microsoft Cognitive Services

Hummingbird

Amazon Kendra

OpenVINO