DataRobot is a platform that provides end-to-end solutions for creative and predictive AI requirements. It offers tools for preparing data, creating and optimizing models, deploying and integrating models, and tracking and evaluating model accuracy.
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DataRobot is a platform that provides end-to-end solutions for creative and predictive AI requirements. It offers tools for preparing data, creating and optimizing models, deploying and integrating models, and tracking and evaluating model accuracy.
Analyze model performance and identify the primary factors.
DataRobot interfaces with a range of platforms, tools, and data sources.
Combining both structured and unstructured data to train models.
Combining both structured and unstructured data to train models
Track the model's bias, ROI, and accuracy in real-time.
Implement and apply models anywhere.
DataRobot, Inc. is a company that specializes in offering automated machine-learning solutions. DataRobot, Inc. DataRobot, a company founded in 2012, provides a platform that helps businesses effectively develop, implement, and manage machine-learning models. The platform automates numerous steps in the machine-learning process, such as feature engineering, model selection, and data preparation. DataRobot aims to make AI accessible by enabling machine learning for users with different skill levels, such as business analysts and data scientists. The company supports clients using AI to drive business insights and decision-making across various industries, including production, retail, healthcare, and finance.
To start, users upload data to the DataRobot platform. When DataRobot’s features are activated, the data is automatically analyzed, patterns are found, and the best machine learning algorithms are chosen for the given task. DataRobot uses the preferred methods to create machine-learning models and then uses cross-validation techniques to assess each model's performance. DataRobot offers users in-depth knowledge about each model's performance through measurements, including accuracy, precision, recall, and AUC. After choosing the top-performing model, the user can use DataRobot's deployment features to put it into production settings.
Data Scientist: Experts in data science who can create and implement machine-learning models effectively using DataRobot's advanced functions.
Business Leaders: Organizational leaders and managers can use DataRobot to facilitate data-driven decision-making and gain a competitive advantage.
Researchers: Researchers in various fields analyze data and create predictive models to help in their studies, and they can use DataRobot.
Enterprise Team: With DataRobot, teams in big businesses can work together to create and implement machine learning models for various use cases, including fraud detection, consumer segmentation, and predictive maintenance.
Business Analyst: Without much coding experience, those who use data analysis to make business choices can use DataRobot to extract ideas and predictions from their data.
To access, visit the official website of DataRobot using a computer browser. Create your account by adding basic information such as your name, email, and company details. After registering and logging in, you can use the DataRobot platform. Uploading your data to the platform is the first step. Create and implement machine-learning models based on your data using DataRobot's automated features. The platform helps you through each procedure step, from preparing the data to applying the model. To help users use the platform, DataRobot often provides support tools like tutorials, documentation, and customer care channels.
Jeremy Achin and Thomas Goday are the founders of DataRobot. DataRobot was founded in 2012 and is headquartered in Boston, MA. Throughout 12 rounds, DataRobot has raised $1.05 billion in investment. With 582 competitors overall, it is ranked 8th.
DataRobot provides a complete platform that automates the whole process of creating and implementing machine-learning models. The platform makes it simple for users to submit and get ready to analyze their data, including feature engineering, categorical variable encoding, and handling missing values. The platform offers insights into model predictions, helping users comprehend the decision-making process of models and identifying key characteristics that influence predictions.
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API | Available,Not Available |
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Community | Available |
Subscription Option | Free,paid with Free Trial option | |
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Subscription Packages | 1 |