Neural Designer implements the most innovative machine learning algorithms in the marketplace. In this post, we describe some of the features that make Neural Designer unique.

Our objective is that you can get the most powerful models from your data.

Explainable AI

One of the main difficulties of machine learning models is that it is difficult to understand what they do. Moreover, their predictions are not easy to interpret.

At Neural Designer, we have worked hard to solve these difficulties. Some of the most remarkable results in Explainable AI are the following:

  • Algorithm description: The platform describes all the configuration options and the results of the tasks so that you have no doubt about which algorithms to use and understand the produced outputs.
  • Model inputs importance: Know the variables that have the greatest impact on the neural network.
  • Sample inputs importance: Know which variables most affect a given prediction.
  • Model exploration: Visualize how the outputs of your model vary as a function of the inputs.

Main screen of the Neural Designer datasets section, highlighting the model visualization.

Feature selection

Many machine learning applications, from customer targeting to medical diagnosis, arise from complex relationships between features (also-called input variables or characteristics).

Feature selection techniques help identify and remove unneeded, irrelevant, and redundant features. Indeed, those variables do not contribute to or decrease the accuracy of the predictive model.

Neural Designer contains the most innovative algorithms to find the optimal architecture for your model:

  • Growing inputs: The growing inputs method starts by calculating the correlation of each input with each output variable.
    This algorithm begins with the most correlated input and keeps adding well-correlated variables until the model’s accuracy stops increasing.
  • Genetic algorithm: The genetic algorithm is a stochastic method based on the mechanics of natural genetics and biological evolution. The method evolves populations of models with different inputs until it obtains the most accurate model. Read more.

Computational performance

Neural Designer is the data science and machine learning platform with the highest computational performance in the market.
As a result, you won’t need powerful computers to build your models, and you will maximize your productivity.

These are the main competitive advantages related to computational performance:

  • Data capacity: The platform is programmed entirely in the C++ language, which stands out for its memory management capacity. This allows you to load datasets several times bigger. Read more.
  • Training speed: Neural Designer has been optimized to boost calculations. It also implements parallelization on CPUs and acceleration on GPUs. As a consequence, you will train your models much faster. Read more.
  • Model accuracy: Neural Designer contains optimization algorithms that use second derivatives to accelerate convergence and increase accuracy, such as the quasi-Newton method and Levenberg-Marquardt algorithm. That means models with greater accuracy. Read more.
  • Energy efficiency: The use of fewer computational resources translates into energy savings. Read more.

On-premises & cloud

There are two main types of computing services: on-premises and cloud. Each has its advantages and disadvantages.

On-premises computing is more convenient for data scientists working with a computer program for a long time.

On the other hand, cloud computing allows access anywhere, anytime, and users can choose the most appropriate instance type for their project.

Therefore, Neural Designer offers these two types of computer services;

  • On-premises: Work natively on your favourite platform: Windows, Mac OS X or Linux.
  • Cloud: Projects with very big amounts of data might require a lot of computational resources. In this case, you can use Neural Designer on a high-performance instance of Amazon Web Services. Read more.

Machine Learning Operations (MLOps)

The concept of MLOps refers to the operationalization of machine learning models.

With neural designer, you can export your models in different programming languages (C, Python, PHP, JavaScript) without requiring any external library, and deploy them into your company’s system in the simplest possible way.


Neural Designer is the most advanced data science and machine learning platform on the market.

Neural Designer contains unique features that allow you to build the most powerful models from your data and deploy them in a simple way.

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