AI ディレクトリ : AI Developer Tools, AI Product Description Generator, Large Language Models (LLMs)
What is DataRobot?
DataRobot is a platform that offers end-to-end solutions for generative and predictive AI needs. It provides tools for data preparation, model building and optimization, model deployment and integration, and monitoring and measuring model accuracy.
How to use DataRobot?
To use DataRobot, you can start by connecting your data and assessing its quality. Then, you can engineer new features and integrate with feature stores. Next, train models using structured and unstructured data, experimenting with different strategies. Once models are built, you can evaluate their performance, identify key drivers, and create customizable apps for decision-making. For production AI, DataRobot helps validate and govern AI assets, deploy and integrate models anywhere, and monitor model accuracy, ROI, and bias in real-time.
DataRobot's Core Features
Connect data and assess data quality
Engineer new features and integrate with feature stores
Train models using structured and unstructured data
Evaluate model performance and identify key drivers
Create customizable apps for decision-making
Validate and govern AI assets
Deploy and integrate models anywhere
Monitor model accuracy, ROI, and bias in real-time
DataRobot's Use Cases
Healthcare and Life Science
Manufacturing
Retail
Financial Services
DataRobot Support Email & Customer service contact & Refund contact etc.
More Contact, visit the contact us page(https://www.datarobot.com/contact-us/)
DataRobot Company
DataRobot Company name: DataRobot, Inc. .
More about DataRobot, Please visit the about us page(https://www.datarobot.com/about-us/).
DataRobot Login
DataRobot Login Link: https://app.datarobot.com/
DataRobot Pricing
DataRobot Pricing Link: https://www.datarobot.com/pricing/
DataRobot Youtube
DataRobot Youtube Link: https://www.youtube.com/channel/UC5fFOfzgxQ9XVqNesi9U0MQ
DataRobot Linkedin
DataRobot Linkedin Link: https://www.linkedin.com/company/datarobot
DataRobot Twitter
DataRobot Twitter Link: https://twitter.com/DataRobot
FAQ from DataRobot
What is DataRobot?
DataRobot is a platform that offers end-to-end solutions for generative and predictive AI needs. It provides tools for data preparation, model building and optimization, model deployment and integration, and monitoring and measuring model accuracy.
How to use DataRobot?
To use DataRobot, you can start by connecting your data and assessing its quality. Then, you can engineer new features and integrate with feature stores. Next, train models using structured and unstructured data, experimenting with different strategies. Once models are built, you can evaluate their performance, identify key drivers, and create customizable apps for decision-making. For production AI, DataRobot helps validate and govern AI assets, deploy and integrate models anywhere, and monitor model accuracy, ROI, and bias in real-time.
How do I use DataRobot?
To use DataRobot, you can start by connecting your data and assessing its quality. Then, you can engineer new features and integrate with feature stores. Next, train models using structured and unstructured data, experimenting with different strategies. Once models are built, you can evaluate their performance, identify key drivers, and create customizable apps for decision-making. For production AI, DataRobot helps validate and govern AI assets, deploy and integrate models anywhere, and monitor model accuracy, ROI, and bias in real-time.
What are the core features of DataRobot?
The core features of DataRobot include data connection and quality assessment, feature engineering and integration, model training using structured and unstructured data, model evaluation and customizable app creation, AI asset validation and governance, model deployment and integration anywhere, and real-time monitoring of model accuracy, ROI, and bias.
What are the use cases of DataRobot?
DataRobot is used in industries such as healthcare and life science, manufacturing, retail, and financial services to accelerate AI adoption and improve decision-making processes.