使用Tensorflow Lite的公司
It is a set of tools to help developers run TensorFlow models on mobile, embedded, and IoT devices. It enables on-device machine learning inference with low latency and a small binary size.
使用Tensorflow Lite的公司列表
curl --request POST \
--url "https://api.theirstack.com/v1/companies/search" \
--header "Accept: application/json" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer <api_key>" \
-d "{
\"company_technology_slug_or\": [
\"tensorflow-lite\"
]
}"Technology
is any of
Tensorflow Lite
员工数384Software DevelopmentTensorflow Lite中置信度
员工数1.1kTechnology, Information and InternetTensorflow Lite中置信度
员工数1RetailTensorflow Lite中置信度
员工数673收入$286kIT Services and IT ConsultingTensorflow Lite中置信度
员工数182k收入$65BIT Services and IT ConsultingTensorflow Lite中置信度
员工数12kSemiconductor ManufacturingTensorflow Lite中置信度
员工数49Semiconductor ManufacturingTensorflow Lite中置信度
员工数22kSemiconductor ManufacturingTensorflow Lite中置信度
员工数33Nursing Homes and Residential Care FacilitiesTensorflow Lite中置信度
员工数513Medical Equipment ManufacturingTensorflow Lite中置信度
我们拥有关于1,660家公司和用户使用Tensorflow Lite的数据。我们的Tensorflow Lite用户和客户列表可供下载，并附有重要的公司信息，包括行业分类、组织规模、地理位置、融资轮次和收入数据等。
技术使用统计和市场份额
如何定位 Tensorflow Lite 用户
- 如何自定义此列表？
您可以根据地理位置、行业、公司规模、收入、技术使用、职位发布等需求自定义此数据。您可以将数据下载为Excel或CSV格式。
- 如何在公司采用此技术时收到通知？
您可以为此数据设置提醒。您可以通过选择您感兴趣的技术开始，当有新公司使用该技术时，您将收到收件箱中的提醒。
- 如何将此数据导入我的CRM？
您可以将此数据导出为Excel文件，然后导入到您的CRM中。您也可以将数据导出到API。
常见问题
我们的数据来源于从数百万家公司收集的职位发布。我们监控公司网站、招聘网站和其他招聘平台上的这些发布。分析职位发布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。
我们每天刷新数据，以确保您访问的是最新的信息。这一频繁的更新过程保证了我们的洞察和情报反映行业的最新发展和趋势。
Tensorflow Lite is a technology developed by Google for machine learning applications, particularly optimized for mobile and edge devices. It is a lightweight version of the popular Tensorflow framework, designed to run machine learning models on mobile and IoT devices with lower computational resources. Tensorflow Lite enables developers to deploy machine learning models on edge devices, allowing for faster and more efficient inferencing without relying on cloud services.
Tensorflow Lite falls under the category of Machine Learning Tools, offering a specialized solution for deploying machine learning models on resource-constrained devices. It provides a framework for developers to implement efficient machine learning algorithms on a wide range of devices, from smartphones to embedded systems. By utilizing Tensorflow Lite, developers can harness the power of machine learning directly on edge devices, enabling real-time inference and processing of data without the need for continuous network connectivity.
The history of Tensorflow Lite dates back to 2017 when Google introduced the technology as an extension of the original Tensorflow framework. The motivation behind developing Tensorflow Lite was to address the growing demand for running machine learning models on mobile and edge devices efficiently. By optimizing the computational performance and memory footprint, Google aimed to make machine learning more accessible and practical for a broader range of applications. Since its inception, Tensorflow Lite has evolved to become a leading solution for deploying machine learning models on edge devices.
In terms of current market share, Tensorflow Lite has gained significant traction within the Machine Learning Tools category. Its efficient performance on resource-constrained devices has made it a preferred choice for developers looking to implement machine learning models on edge devices. With the increasing adoption of edge computing and IoT applications, the market share of Tensorflow Lite is expected to grow further in the future as more industries leverage the power of machine learning at the edge.