Automatic Machine
Learning in Python
Automatic Machine
Learning in Python
Automated Machine Learning in Python
Automated Machine Learning – AutoML – is the key technology for predictive analytics using artificial intelligence. It is very easy to work with our ClearVu Intelligence Python Pro and to use this technology now in Python in a very comfortable way. This allows for accessing and using the powerful ClearVu Intelligence tool within Python.
Automated Machine Learning in Python
Automated Machine Learning – AutoML – is the key technology for predictive analytics using artificial intelligence. It is very easy to work with our ClearVu Intelligence Python Pro and to use this technology now in Python in a very comfortable way. This allows for accessing and using the powerful ClearVu Intelligence tool within Python.
State-of-the-art machine learning algorithms are available:
State-of-the-art machine learning algorithms are available:
Automated hyperparameter optimization for generating the best model
The key idea in automated machine learning is to tune the parameters of the machine learning algorithms for the specific data set of the end user. These parameters are called hyperparameters, and the tuning process creates a complicated optimization problem. ClearVu Intelligence for Python embeds divis’ proprietary hyperparameter optimization algorithm for solving this optimization problem automatically, as efficiently as possible and invisible to the user.
All model types or user-selected model types can be trained and their hyperparameters optimized for the given data set. The selection of the final best model is then based on the measured average prediction performance of the models.
Automated hyperparameter optimization
for generating the best model
The key idea in automated machine learning is to tune the parameters of the machine learning algorithms for the specific data set of the end user. These parameters are called hyperparameters, and the tuning process creates a complicated optimization problem. ClearVu Intelligence for Python embeds divis’ proprietary hyperparameter optimization algorithm for solving this optimization problem automatically, as efficiently as possible and invisible to the user.
All model types or user-selected model types can be trained and their hyperparameters optimized for the given data set. The selection of the final best model is then based on the measured average prediction performance of the models.
Python Package and API Documentation
The ClearVu Intelligence Python Pro uses widely accepted python packages for data handling and an interface for easy parallelization. An example is demonstrated in the API documentation. The API documentation provides you with all further information regarding the programming interface in Python, with functions for fitting, comparing, loading, saving and exporting models.
Python Package and API Documentation
The ClearVu Intelligence Python Pro uses widely accepted python packages for data handling and an interface for easy parallelization. An example is demonstrated in the API documentation. The API documentation provides you with all further information regarding the programming interface in Python, with functions for fitting, comparing, loading, saving and exporting models.
Price
Price
Other Software
Other Software
Our software ClearVu Intelligence provides optimal support for all applications of predictive analytics, product- and process optimization. The flexibility of the system also support a direct integration into existing workflows and interfacing with production processes.
ClearVu Design Space supports you in the design of systems and components in the automotive industry. There are many restrictions to comply with and ClearVu Design Space provides optimal flexibility for the identification of design variants.
The Excel Add-In enables you in just a few clicks to use Automated Machine Learning directly in Excel to build forecasting models for your data sets. The resulting predictive model can be used as a cell function for predictions and the model can be analyzed and visualized further.
Contact
How to contact us
Telephone
+49 231 97 00 340
Address
Joseph-von-Fraunhofer-Straße 20,
44227 Dortmund, Germany
Contact
How to contact us
Telephone
+49 231 97 00 340
Address
Joseph-von-Fraunhofer-Straße 20,
44227 Dortmund, Germany