In the past, humans stored and retrieved data in their brains. As the volume of data grew, methods of storage and retrieval changed. Data was stored in paper, then later in systems. Today, the landscape of data has changed, due to exponential growth, and humans and past systems cannot make sense of it on their own. This has called for increasingly automated systems that can adapt to the ever-changing data without being programmed, which has been made possible by machine learning.

What is machine learning?

Machine learning is a branch of Artificial Intelligence (AI) that gives systems the ability to learn automatically and improve experience without explicit programming. It is based on the idea that systems can identify patterns in data, learn from them, and use them to make decisions with minimal human intervention.

How machine learning works

Machine learning has three main categories namely:

Supervised learning

Here the machine learns using past data which helps it to make decisions and predictions upon encountering new data. Supervised learning is further divided into:

  • Classification: Here, data is divided into different categories based on past data. For instance, sorting of spam emails relies on training using previous data.
  • Regression: Values for input are predicted based on previous information. Sounds similar to classification, right? Regression not only classifies observations, but it also estimates values, for instance, the value of a house you are trying to buy.

Unsupervised learning

The system uses input data to detect patterns, similarities, and anomalies. It is divided into:

  • Clustering: the machine assigns subsets (clusters) to a set of observations that are similar to one another based on a parameter. Telecom providers use clustering to divide an area and find the optimum place for a cell tower that will ensure connectivity for everyone.
  • Association: a machine identifies patterns between different variables. For instance, the patterns that help websites to recommend items for customers in e-commerce.

Reinforcement learning

Systems make dynamic decisions in a changing environment, based on the rewards and punishment that they received for the last action they performed.

Where is machine learning used?

You use machine learning every day, even without noticing it. Here’s how machine learning is used:

Online recommendations

Machine learning gives you personalized recommendations based on previous shopping patterns, or who you follow on social media.


Machine learning identifies patterns, analyses data, predicts problems, and makes decisions increasing transport efficiency. Also, it helps apps such as Uber to minimize your waiting time, determine the price of your ride, and minimize detours.

Spam filters

Machine learning powers the spam filters in email inboxes.

Healthcare industry

This technology is used widely by medical experts to analyze data and identify trends and red flags that can help improve their services.

To get the most out of machine learning, you should pair the best algorithms with the best tools and processes. The answer to the question “should I leave my VPN on all the time” should always be yes, since you have sensitive data that is prone to hacking on social media and other platforms.

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