Vitriol is an easy-to-use tool for your machine learning needs. It can analyze and visualize your data, build models automatically. There is lots of machine learning in it.
Use Vitriol from anywhere you want, with any device.
Process your data from different sectors.
Create different user roles according to company needs.
Visualize your data and models with various graphs.
Vitriol is an automated online machine learning tool, intended to be an equipped data scientist. It uses machine learning & data mining techniques for data processing and predictive modeling.
Vitriol offers different data processing functionalities. It cleans your data from unnecessary and inaccurate fields. It completes your data with statistical & machine learning based imputation methods.
It creates machine learning models. Since the search space created by the number of machine learning algorithms and their parameters is vast, selecting a machine learning model is not an easy task, even on a small data set. Vitriol is smart. It chooses the most appropriate machine learning model for a learning problem by utilizing past learning experience instead of trying solutions one by one based on intuition. Moreover, Vitriol improves itself with each problem it solves.
Vitriol visualizes data distributions and models it created with 2D and 3D graphs for better understanding.
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The companies need to develop the most appropriate strategy by assessing existing opportunities, using the resources at the right time and right place and focusing on the right target in order to survive in the business world. Making better decisions that determine the future of the companies, institutions or organizations is possible only by selecting the appropriate data analysis technique which serves the intended business purpose in a specific case with some particular restrictions.
Analyzes your data to find out table structures and field characteristics. Statistical calculations are performed to help user understand the data and support decision making.
Detects invalid, irrelevant and meaningless data points and decides on the best action to resolve the situation. It purifies your data by removing outliers & inaccurate values. It can choose to drop a field or complete it with statistical & machine learning based imputation methods.
Creates predictive models fitting your data. It considers numerous possible algorithms and chooses the one expected to perform best. In a reasonable time.
Provides visualizations such as charts and graphs. It makes understanding the data and the generated models easier.
Department of Computer Engineering Middle East Technical University Inonu Bulvari, 06800, Ankara TURKEY
Phone Number: (123) 456 7890
Fax Number: (123) 456 7890