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Quickly train ML models
using standard queries
Reduce the need for time-consuming ETL’ing, model generation, comparison, and tuning by applying Machine Learning to your datastore. Build predictions directly into your existing tables and query them using simple SQL.
Classic Applied ML
weeks to months
Modern Applied ML
minutes to hours
"We believe MindsDB can quickly establish a position as the leading solution for developers out there wanting to use ML/AI to include fascinating capabilities in their applications."
Patrik Backman
Founder of MariaDB
AI Tables
Get the predictions you need as simple tables in your database.
Use your data at the source to train & deploy Machine Learning models and get the predictions you need as tables. Query the results anytime in seconds as if they were existing tables.
AI Tables are created with simple queries inside the database or data store and contain predictions generated in real-time by the models.
MindsDB looks and acts like a database and thus seamlessly interacts with your current database and BI tools.
Use the data you have
MindsDB works right at your data source, on various tabular data such as numbers, categories, dates/timestamps, text (including lengthy text, e.g., articles), and images, so your use cases are limitless.
Instant Deployment
Because MindsDB acts like a database once you find the right model, deployment takes just a matter of seconds. Setup automated retraining as you collect more data to ensure you always have the latest and most accurate model in production. This is all handled behind the scenes you don't have to.
Use Fewer Resources
Our codeless interface guides users through the full end-to-end machine learning lifecycle, making it easy for anyone on your team to build models and reliably incorporate them into broader applications.
Automated Machine Learning
Let MindsDB train and test the best model for your problem.
Add predictive machine learning to your analytics projects without changing your existing workflows, hiring additional teams, or learning new tools or programming languages with MindsDB Automated Machine Learning.
Automate the process of applying machine learning with our state-of-the-art AutoML.
- Train, Evaluate, Select and Optimize models automatically
- No Data Science skills required
- Choice of interfaces: Python native or SQL AI-table implementation
Effortless Model Building
MindsDB automates the time consuming steps of creating a machine learning model. Including, feature engineering & encoding, training, evaluation, selection and optimization to create the best model for your given problem. This can all be achieved with no data science skills, so your existing team can handle the job.
Saves Money
MindsDB AutoML enables significant cost savings by enabling your existing team of developers, data analysts and DB administrators to perform highly technical machine learning by levering the existing tools they use day-to-day.
Saves Time
MindsDB AutoML speeds up the R&D process by moving from Idea to deployable model faster. We do this by automating many of the tedious components of model creation. Experiment with your data and deliver valuable insights in a fraction of the time.
Explainable AI
Understand, interpret and trust your results.
Explainable AI (XAI) helps you to understand and interpret the results generated by Machine Learning Models. With it you can understand the strengths and weaknesses in your data and within the predictions themselves. Understand how the model will behave in production and help other stakeholders understand your models and the results they generate.
Trust for you and your team
With MindsDB Explainability Machine Learning is no longer a black box. Derive insights from your data and model to instill confidence and trust in the results. Our Graphical User Interface visualizes the output so it can be shared with a variety of stakeholders. You can now answer. Why does the model preform the way it does? How can we improve it? What factors matter most?
Strengths and weaknesses in your data
MindsDB does a full statistical analysis on your data before it begins creating a model. This enables you to determine the strengths and weaknesses in your data. Identify outliers, missing values and even correlation to ensure the correct data is fed into MindsDB.
See how MindsDB works
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