Machine Learning

What is Machine Learning?

Machine learning is a type of artificial intelligence that provides computers with the ability to learn without being explicitly programmed.  Machine learning focuses the development of programs and apps that change when exposed to new data. This discipline reports such sciences as mathematical statistics, analysis, and optimization techniques.

The process is similar to data mining, as both are primarily aimed for looking through large amounts of data to try and find a pattern. The major difference is that data mining is to find patterns which humans can see and make a decision, while machine learning is finding these patterns and then the computer deciding what to do on its own.

A machine learning algorithm is normally classified as either supervised or unsupervised. In the case of supervised algorithms, the program is given ‘training data’, which the program then created an inferred function used for mapping new examples. A commonly used example of this is handwriting recognition. An unsupervised algorithm will try to find correlations without any external inputs other than the raw data, for example trying to group together similar pictures.

Real World Uses in App Development

  1. Face detection: Snapchat’s filters
  2. Face recognition: Automatic tagging in Facebook
  3. Image classification: Google image search
  4. Speech recognition: Siri and Alexa being able to respond to your voice
  5. Anti-spam: Spam filters have learnt from years of data to stop spam being delivered to your inbox.
  6. Recommendations: Your Facebook news feed is specialized for you based on your previous likes and views.
  7. Weather forecast: Machine learning is applied in weather forecasting software to improve the quality of the forecast.


The Future

Machine learning’s possibility are vast and in the future will cover huge amounts of our personal lives. We could gradually get rid of many routines that are needlessly consuming valuable time.

Some areas that will be improved due to machine learning:

  1. Self-driving cars: Although this technology is available in part, in the not too distant future cars will be completely self-driving. Self-driving cars have already shown to be safer and have fewer crashes than their human counterparts, and this is only going to improve.
  2. Healthcare: Inspection, diagnosis and treatments will all be possible without actually having to see anyone. A well-developed algorithm with enough data will be able to determine what’s wrong with you quicker and more reliably than a person.
  3. Law: Machine learning will lack the creativity of some of the top lawyers, but in the majority of cases (if the data was made available), an algorithm could create a defense based on previous similar examples.
  4. Accounting: Accounting could be boiled down to someone refining algorithms for law changes and reviewing the output, there would be no need for any of the manual work currently done.


Machine learning is becoming a large part of our lives, while remaining virtually unnoticed in everyday use. We believe that such technologies allow evolving, making everyday life easier, pushing technology progress forward.

The next stage is to ensure security on the network, by more accurately filtering unwanted or inappropriate content, and ensuring safety on the roads, at airports or other places.

For general mobile development you should consider more accurate geolocation, recommendations of places to relax or companies providing different kinds of commodities and services. This will become increasingly important as more and more companies inserting elements of machine learning into the code.

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