使用MLflow的公司
MLflow is an open source platform for managing the end-to-end machine learning lifecycle.
使用MLflow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\": [
\"mlflow\"
]
}"Technology
is any of
MLflow
员工数14k收入$600MSoftware DevelopmentMLflow高置信度
员工数412k收入$45BProfessional ServicesMLflow中置信度
员工数68k收入$4.8BIT Services and IT ConsultingMLflow中置信度
员工数738k收入$63BBusiness Consulting and ServicesMLflow中置信度
员工数730k收入$27BIT Services and IT ConsultingMLflow中置信度- 员工数700ConstructionMLflow中置信度
员工数244kFinancial ServicesMLflow中置信度
员工数89k收入$9.5BIT Services and IT ConsultingMLflow中置信度
员工数148k收入$33BSoftware DevelopmentMLflow中置信度
员工数42k收入$26BBiotechnology ResearchMLflow中置信度
我们拥有关于22,686家公司和用户使用MLflow的数据。我们的MLflow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 MLflow 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。
MLflow is an open-source platform designed to manage the end-to-end machine learning lifecycle. It provides a framework to streamline the machine learning process, from experimentation to deployment, enabling Data Scientists to track experiments, package code, and deploy models efficiently. With its suite of tools and libraries, MLflow aims to simplify the complexities associated with machine learning development.
MLflow falls under the category of Machine Learning Tools, focusing on enhancing the development and deployment of machine learning models. It offers features such as experiment tracking, model packaging, and model serving, catering to the needs of Data Scientists and Machine Learning Engineers. By providing a centralized platform for managing the machine learning lifecycle, MLflow contributes to improved collaboration and productivity within data science teams.
Founded in June 2018 by the Databricks team, including the creators of Apache Spark, MLflow was established with the goal of addressing the challenges faced by organizations in operationalizing machine learning projects. The primary motivation behind the creation of MLflow was to offer a standardized approach to managing, deploying, and scaling machine learning models effectively. Since its inception, MLflow has gained significant traction in the machine learning community, attracting a growing user base and fostering a vibrant ecosystem around the platform.
In terms of current market share, MLflow has seen widespread adoption across various industries, thanks to its robust set of features and integrations with popular machine learning frameworks. As more organizations recognize the importance of streamlining their machine learning workflows, MLflow is poised for continued growth in the future. With advancements in technologies such as AI and data science, the demand for efficient machine learning tools like MLflow is expected to rise, further solidifying its position in the market.