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AWS DeepRacer?

Accepted Answer

AWS DeepRacer is a technology developed by Amazon Web Services AWS that falls under the category of Machine Learning Tools It is a fully autonomous 118th scale race car designed to help developers of all skill levels learn about reinforcement learning machine learning and 3D simulation By providing a handson experience with a physical vehicle AWS DeepRacer allows users to experiment with different reinforcement learning algorithms and techniques in a fun and engaging way

AWS DeepRacer was founded by AWS in 2018 with the aim of democratizing reinforcement learning and making it more accessible to a broader audience The motivation behind the creation of DeepRacer was to empower developers researchers and enthusiasts to learn and experiment with machine learning in a practical and interactive environment By combining the thrill of racing with the complexity of reinforcement learning AWS DeepRacer offers a unique platform for individuals to enhance their skills and knowledge in this cuttingedge field

In terms of current market share AWS DeepRacer has gained significant traction within the machine learning tools category since its inception Its innovative approach to combining physical racing with machine learning education has garnered attention and interest from various industries and professionals With the increasing demand for AI and machine learning solutions across different sectors AWS DeepRacer is expected to continue growing in market share as more organizations look to leverage the power of reinforcement learning in realworld applications As the technology evolves and new features are introduced AWS DeepRacer is likely to solidify its position as a leading tool for experiential learning in the field of machine learning

Question 4

如何获得使用AWS DeepRacer的公司的最新列表？

Accepted Answer

您可以访问 TheirStack.com，获取使用 AWS DeepRacer 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

AWS DeepRacer 有多少客户？

Accepted Answer

截至目前，我们拥有关于 5 家使用 AWS DeepRacer 的公司的数据。

Question 6

谁在使用AWS DeepRacer?

Accepted Answer

AWS DeepRacer 被广泛应用于包括 "It Services And It Consulting", "It Services And It Consulting", "Financial Services", "Software Development" 在内的各个行业的各种组织中。欲了解所有使用 AWS DeepRacer 的行业的完整列表，请访问 TheirStack.com。

Question 7

哪些公司使用AWS DeepRacer?

Accepted Answer

一些使用AWS DeepRacer的公司包括株式会社DNPデジタルソリューションズ, Acuity Inc, Amazon Web Services, Capco, Sunixa Solutions以及更多公司。您可以在TheirStack.com上找到使用AWS DeepRacer的5家公司完整列表。

Question 8

哪些国家使用AWS DeepRacer最多？

Accepted Answer

根据我们的数据，AWS DeepRacer 在 日本 (1 companies), 英国 (1 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AWS DeepRacer的公司？

Accepted Answer

您可以在TheirStack.com上搜索AWS DeepRacer，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
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Company name Industry Size Revenue
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Company name Industry Size Revenue
Company name Industry Size Revenue
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公司	国家	行业	雇员	收入	技术
株式会社DNPデジタルソリューションズ	日本	It Services And It Consulting	9		AWS DeepRacer
Acuity Inc					AWS DeepRacer
Amazon Web Services		It Services And It Consulting			AWS DeepRacer
Capco	英国	Financial Services	6.5K	$720M	AWS DeepRacer
Sunixa Solutions		Software Development			AWS DeepRacer

使用 AWS DeepRacer 的公司

如何针对AWS DeepRacer用户进行定位

使用 AWS DeepRacer 的公司

如何针对AWS DeepRacer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AWS DeepRacer?

什么是AWS DeepRacer?

如何获得使用AWS DeepRacer的公司的最新列表？

如何获得使用AWS DeepRacer的公司的最新列表？

AWS DeepRacer 有多少客户？

AWS DeepRacer 有多少客户？

谁在使用AWS DeepRacer?

谁在使用AWS DeepRacer?

哪些公司使用AWS DeepRacer?

哪些公司使用AWS DeepRacer?

哪些国家使用AWS DeepRacer最多？

哪些国家使用AWS DeepRacer最多？

如何找到使用AWS DeepRacer的公司？

如何找到使用AWS DeepRacer的公司？

AWS DeepRacer 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 Comprehend

Amazon Textract

Tensorflow Lite

Microsoft Cognitive Services

Hummingbird

Amazon Kendra

OpenVINO

Apache Mahout

DeepSpeed

Numba

Gradio