What is DataRobot?

Machine learning models can be deployed, accelerated, and automated using DataRobot AI platform. Building predictive analytics with DataRobot minimizes risk, expenses, and time for quicker and better decisions. Provides a growing collection of the most up-to-date algorithms and best practices for choosing and deploying models, thus empowering data scientists.

What are the main benefits of DataRobot?

Impact the Bottom Line: Convert data and analytics into useful information so you can confidently make suggestions. Increased control over the data science process and improved models leads to immediate cost reductions as well as potential new business prospects.

Accelerate Productivity: Get value from data more quickly than any other method available. DataRobot creates and compares models using hundreds of the most recent machine learning algorithms enabling users to effectively use the best model to determine a course of action.

Amplify Human Intuition: Automate recommended practices to expand your data science skills. Business analysts and data analysts with profound expertise in the domain will develop their skills and increase their organization's capacity for data-driven decision making at a reasonable cost and in short time.

Principal benefits of DataRobot for specific roles:

• Business Analysts: Business analysts looking to integrate machine learning into their existing processes have an advantage thanks to DataRobot's ability to automate many of the regular tasks now carried out by data scientists.
• Data Scientists: With a variety of data engineering best practices, automated with custom-coded pipelines, increase velocity for important jobs. Create accurate models with complete modification and experimentation flexibility in a fraction of the time.
• IT Operations: Whether you need real-time forecasts, batch deployments, or scoring on Hadoop, you can quickly and easily deploy machine learning models into production.

DataRobot main features:

1. Augmented Intelligence
2. Data Engineering
3. AutoML
4. Automated Time Series
5. Notebooks
6. MLOps
7. Continuous AI
8. No-Code AI Apps
9. AI Applications
10. Decision Intelligence Flows
11. Bias and Fairness
12. Explainable AI