This technique is used to solve problems and implement functions whose difficulty and complexity make the use of traditional algorithmic methods extremely time-consuming, expensive and therefore very expensive. In a particular way, solutions with a high degree of difficulty, such as e.g. decision support, text and image analysis or prediction can and are effectively implemented using ML methods. The Whiteaster team can help you to adapt machine learning to your project, which will give you a market advantage.
To simplify a comprehensive issue, machine learning is a series of methods and solutions that allow to teach an ML module on the basis of examples that represent a set of learners or on the basis of feedback that assesses the quality of such module’s work. As part of our partnership we will explain to you how it works and what it can be used for, and in particular how to implement it in your solution.
The classic approach to programming is the implementation of algorithms – closed sets of rules written as code in the programming language. They cover all possible data processing paths and rules. The programmer must foresee all possibilities and be precise in the implementation of these rules.
Machine learning is something otherwise. The programming process could be concluded as a training model with examples. The machine learns by itself, “looking” at data samples, just as our brain learns from our experience. So we do not say exactly how to process the data, we just say what the right answer is and we simply let the model find the patterns inside the data itself.
So, it is still similar to normal programming, but the approach is changing. We also have to remember that machine learning is not some magic technique that works in a few minutes. There are many complicated processes, but if we do them correctly, the results can be amazing.
Systems using so-called computer vision are widely used.
We use them in everyday life by photographing ourselves and others using for example a smartphone. However, it is not only photography that uses this area of artificial intelligence.
Large companies that care about the safety of their employees and the confidentiality of company data choose modern systems based on the mechanism of computer vision.
Nowadays, we also use image recognition when cataloguing monuments, museum exhibits or simply a wide range of wholesalers or shops.
This area is also valued in medicine, as it is the basis for the development of applications for image diagnostics, improving the diagnosis of various types of diseases.
At Whiteaster we have experience in processing and analysing large data sets. By using advanced analytical mechanisms – Machine Learning – which is one of the areas of artificial intelligence, systems are created that learn how to analyse and interpret vast amounts of data. Solutions based on Machine Learning adapt to the needs of their users as much as possible and effectively improve the work of any business.
As an IT company we offer many services in the field of machine learning. Our goal is to provide you with access to technology that can make a significant contribution to your business.
We invite you to familiarize yourself with examples of realizations in this area.
The project consisted of the following modules :
Liveness detection (detection of user's life span)
User age estimation
Age verification with the use of identity card
User verification with ID card
The aim is to bring closer the process of creating, selecting algorithms and evaluating data in order to achieve the intended goal of improving and accelerating decision-making.
The goal of the research project was to verify the possibility of recognising emotions based on human reactions. The project investigated 5 key emotions: fear, sadness, dread, joy and neutral state.