Enable machine learning automation

Recently, it has become possible to actually introduce and utilize artificial intelligence (AI) in various aspects of business, such as sales forecasting, failure prediction of production equipment, and quality control, and to achieve great results. However, when introducing AI, there is a problem that "there are not enough data scientists and machine learning engineers". Each company is working on recruiting jobs and training AI human resources, but the reality is that AI is becoming a barrier to the introduction of AI without catching up.

The AI tool "Driverless AI", which converts the know-how of the world's top data scientists into software, will help to compensate for this shortage of human resources and promote the use of AI in companies. It automates and accelerates the work of creating machine learning models, which is usually done by data scientists.


Three strengths of Driverless AI

1. High speed

High-speed calculation using GPU greatly reduces the time required for model creation. The created model can be used immediately on site.


2. High precision

The know-how of the world's top data scientists has been turned into software, and high-precision model construction is realized simply by inputting data without having advanced skills.


3. Trust

You can visually interpret the factors that influenced the forecast results, so you can fulfill the accountability required in business. Avoid black Box AI.



How to use 3 easy steps

*The three parameters for accuracy, time, and model explainability, as well as parameters for time-series data, can be adjusted as needed.



Key Features of Driverless AI

● Automatic visualization of data

You can intuitively understand your data and get an overview of your data before building a model.

Outliers/histograms/correlation graphs/heat maps, etc.


● Automatic feature design

It automates feature engineering that relies on the know-how of data scientists.

Users do not require advanced skills.

● Visualization of model decision reasons

You can visually interpret the parameters that influenced the prediction results. It is possible to explain not only the entire model but also each cluster and individual result, preventing AI from becoming a black Box.

K-LIME/Shapley/Variable Importance/Decision Tree/Partial Dependence

● Model result report creation

It automatically generates the reports necessary to explain the created model to the business side and management.

Details of the data used to create the model/algorithm/model tuning flow/importance of feature values/feature design techniques, etc.

● Generate execution module for Python/Java environment

Automatically generate execution modules for Python and Java environments for implementing the created model in existing or new internal systems.

● Support for time-series data

You can also create models for time series data. Automatically detect the order of time.



Various challenges in the manufacturing industry



Solving challenges with Driverless AI

When considering using AI to solve business problems, have you ever run into bottlenecks due to lack of resources or speed?
At Macnica, we not only provide and support Driverless AI, a machine learning automation tool that can be easily used without advanced skills, but we also help customers solve their business challenges by listening to any problems they may have in the processes before and after the AI.