Machine learning consulting services

Machine learning is a branch of artificial intelligence based on developing algorithms and models that allow computers to learn patterns and make decisions or predictions based on those patterns identified in the data.

Machine learning is a branch of artificial intelligence based on developing algorithms and models that allow computers to learn patterns and make decisions or predictions based on those patterns identified in the data.

How do we implement a machine learning solution in companies?

YusApi effectively applies machine learning techniques to help our clients make intelligent decisions and eliminate repetitive processes. Our implementation approach follows a meticulous and results-oriented process.

This is the implementation process

Problem definition

Understanding the problem, defining the objectives we want to achieve with machine learning

Data collection

We collect and prepare the data. We pre-process the data to remove outliers, missing values or errors.

Selection of characteristics

We select the variables to be used to train the model. We identify the key features to make accurate predictions.

Data division

We divide the data into training, validation and test sets.

Algorithm selection

The most appropriate machine learning algorithm is selected, depending on the problem, the nature of the data and the objectives to be achieved.

Model training

During training, the model adjusts its parameters so that it can make accurate predictions on unseen data.

Evaluation of the model

We use specific evaluation metrics to measure precision, bias, variance, etc.

Adjustment of the model

We select different values, explore different model architectures and perform regularisation techniques.

Deployment of the model

We deploy it in a production environment where real-time predictions can be made on new data.

Monitoring and maintenance

The performance of the model in production is monitored and periodic adjustments are made to maintain performance.

Diapositiva anterior
Diapositiva siguiente

Examples of machine learning solutions

From documents

We capture data from any type of document with any extension where such files have a large volume of data.

From databases

We have methodologies that allow us a direct connection with data warehouses, which allows us to integrate our own APIs to automate this process.

From sensors

If your business has sensoristics either in the production process or in the product quality process, we can extract this data to help you make valuable decisions.

From business applications

Data generated by business management software such as CRM, ERP or WMS (Warehouse Management Systems).

Do you want to adapt machine learning to your company?

Let us know your project!