The guided path to faster, better data insights
Rulex Enhanced AutoML expands the potential of Rulex Platform, making data insight quick and easy to obtain thanks to a guided workflow.
It takes care of all those time-consuming tasks you need to perform to get your data ready for machine learning operations: data preparation, pre-processing, feature selection, and model creation.
Rulex’s AutoML is enhanced thanks to its outstanding automation of advanced pre-processing and data preparation tasks. It also provides a wide range of algorithms to choose from: Rulex’s powerful eXplainable AI (Logic Learning Machine), Support Vector Machine, Decision Trees, and many others.
Why choose Rulex Enhanced AutoML
Benefits for data scientists
Save time in ML steps: Save time in all the phases of workflow creation, dedicating more energy to analyzing the results. Our solution is also extremely fast in the deployment phase, so you can see results fast, evaluate the performance of multiple models, and optimize them if necessary.
Customize in depth: While benefiting from fully automated machine learning, the process is not black box. This transparency leaves ML gurus freedom to tweak the workflow options and analyze the results at each step.
Benefits for business users
Make work easy: Launch your workflow in seconds by simply choosing the outcome you want to predict. All the complexity inherent in data preparation, pre-processing, and model creation tasks is taken care of by out automated solution.
Speed up business results: Create a model in just a few steps and try it out on new data straight away. By saving valuable time in the deployment phase, you can get results quickly and achieve business goals faster.
Why Enhanced AutoML revolutionizes your data value chain
1. Data analysts and business users spend 80% of their time in preparing and understanding data.
2. The choice of algorithm is entrusted to expert data scientists.
3. The time dedicated to result analysis is marginal compared to other more time-consuming tasks.
Rulex Enhanced AutoML
1. Data preparation is handled by outstanding pre-processing AutoML functionalities, and data scientists intervene if necessary.
2. Rulex’s LLM is used by default to get optimum results, but different or even multiple models can be tried out and evaluated for performance levels.
3. Stakeholders can focus their efforts on refining the model and analyzing the results. This fosters collaboration between data scientists and business experts.