Artificial Intelligence & Machine Learning

Applications of artificial intelligence and machine learning are increasingly becoming part of everyday life. We help modern businesses access the many and rapidly growing uses of AI and ML applications.

  • Artificial Intelligence

    Advances in computing have seen computers gradually become more powerful and portable, with the aim that one day machines could eventually process information as quickly and effectively as a human. Artificial Intelligence (AI), a technology previously only described in science fiction, is increasingly becoming part of everyday life, with the development of modern digital personal assistants, entertainment recommendation services, consumers behaviour prediction algorithms, self-driving vehicles and more.

  • Machine Learning

    Machine learning is a field of artificial intelligence where the objective is to achieve fast, effective pattern recognition based on statistical mathematics, granting computers the ability to find solutions to real-life issues.

    In conventional software development, programmers typically follow a “top-down” approach. This is where subject specialists and business analysts set out the desired behaviour, they want the software engineers to code.

    With machine learning, conventional methodology is turned on its head. Data scientists and ML engineers collect, scrutinise and transpose real-world information. Based on those data observations, engineers create computer models that deduce how real-world entities will act.

Applying AI/ML

Machine learning applications are gaining the market, while the following usages already proved its benefits:

  • Anticipation of values and tendencies by evaluating links across variables such as item demand, sales figures and promotion returns.
  • Forecast classifications and classify new information such as image cataloguing and text sentiment analysis.
  • Revealing structure and dividing related information points into relevant clusters such as customer segmentation, consumer preference and market price.
  • Detecting the anomalous data needed to determine credit scores. Identifying fraudulent behaviour and abnormal equipment readings, and anticipate system failure and downtime.
  • Analysing pre-existing texts to produce chatbots able to answer people’s questions.

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