G2

佳

佳豪 .

researcher

Mid-Market (51-1000 emp.)

6/7/2022

"The ceiling of a one-stop data science platform integrating multiple functions"

5/5

What do you like best about DataCanvas?

DataCanvas is a versatile, end-to-end machine learning platform for data science teams. As an end-to-end automated modeling platform, DataCanvas APS uses AI technology to deliver efficient, agile responses to business needs, enabling model development and application to align with industry scenarios, and addressing the challenges of generating, managing, and operating multiple business models on a large scale. Provide unified standard automation modeling capabilities and model lifecycle management functions, realize the operator open source to users, enabling enterprise customers to build independent AI capabilities. Review collected by and hosted on G2.com.

What do you dislike about DataCanvas?

DataCanvas is well designed with no obvious flaws. Review collected by and hosted on G2.com.

Recommendations to others considering DataCanvas:

Whether you are an engineer from an enterprise or a developer/student from a research institution, you can consult DataCanvas for data science and ML development. Assess your own situation, including the requirements for the data science platform for each business scenario, the hardware and technical architecture, and the skill level acquired by employees. If you're going to build a data science platform, you should look to DataCanvas for advice. They have a lot of experience in this area, and they can offer the help of experienced data scientists. It offers a full range of autonomous AI capabilities, independent of specific hardware or algorithm providers. We hope that this product can continue to be optimized and upgraded, and keep up with the latest artificial intelligence technology, so our company will continue to upgrade the platform. Review collected by and hosted on G2.com.

What problems is DataCanvas solving and how is that benefiting you?

DataCanvas enables developers and data scientists to quickly and efficiently build, train, and deploy machine learning models of any size, with rich feature analysis and presentation capabilities. Review collected by and hosted on G2.com.