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Machine learning

Machine learning, machine learning methods are already present in more solutions than you might think, including those we use every day.

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.

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What is machine learning?

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.

Examples of machine learning uses

  • Image recognition

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.

  • Speech and voice recognition
    Application in ASR (Automatic Speech Recognition) devices, i.e. intelligent solutions enabling e.g. to control the house/office with voice commands.
  • Handwriting readout
    OCR (Optical Character Recognition) systems facilitate the work of the administration, freeing the employees from the repetitive work and allowing them to focus on the main tasks, which affects the efficiency of the team.
  • Text analysis
    This means that it is useful in administration, editorial offices and publishing houses to verify punctuation and syntactic errors and to interpret the content.
  • Determining the route
    Taking into account the volume of traffic, current obstacles and the preferences and habits of GPS application users.
  • Content recommendation systems
    Used in the E-commerce industry and in all social media.
  • Diagnostics
    Dedicated to technical and medical industries.
  • Forecasting
    It is used to forecast faults and anomalies in industry, weather conditions or financial exchanges.
  • Regulation and control
    Used from industrial automation to driving vehicles and robots.
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Why Whiteaster?

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.

  • Consultancy for machine learning
  • Construction of specialized, web and mobile applications that use ML methods
  • Support in the field of machine learning – in terms of solutions, developed applications or R&D work
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We have extensive experience in implementing systems based on Machine Learning.

We invite you to familiarize yourself with examples of realizations in this area.

Face recognition, age estimation, verification – ML

The project consisted of the following modules :

Face detection
Liveness detection (detection of user's life span)
User age estimation
Age verification with the use of identity card
User verification with ID card

An example of implementing machine learning processes in the financial industry

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.

Technology for recognising human emotions in the virtual reality environment (VR) based on machine learning

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.

Are you ready to develop your company?

Share your idea for the project, we will evaluate it reliably

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Technology
python
OpenCV
pytorch
dash
keras
pandas
hadoop
tensorflow
AWS
pasted
scikit

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