How Machine Learning Works

Machine learning is a subset of artificial intelligence, or AI, that allows computer systems to improve and learn without user intervention. In the past few years, AI has brought us better web searches, autonomous vehicles, a deeper knowledge of the human genome, and much more. Machine learning is woven into every part of our lives, and we are often unaware it’s being used. Read on to learn about machine learning and how it works.

Machine Learning: What Is It?

In the simplest terms, machine learning is about making predictions using available data. Its evolution arose from the recognition of patterns and the application of algorithms. As computer models are given new data, they adapt independently. When a machine learning company creates algorithms, computer systems find patterns, create new models, and offer predictions in the absence of pre-programmed rules.

Different Types

The goal of machine learning is to help computers learn and adjust without our help. The learning process starts with data or observations, which help machines find patterns and make better decisions. Below, we’ll break down the most common approaches.

  • In supervised learning, algorithms are developed using pre-set examples. After the computer has been trained sufficiently, it can compare output with a target, find errors, and adapt its model accordingly. Supervised learning is often used in applications that make predictions based on historical data.
  • In unsupervised learning, algorithms use non-labeled and unclassified data. The system isn’t programmed with the right answer, which forces the algorithm to decide what it’s seeing. For example, it can help companies narrow their target markets during promotional campaigns.
  • In semi-supervised learning, machines use a combination of the above strategies. The method is often used in facial recognition apps, as the acquisition of unclassified data is less resource intensive.
  • Reinforcement learning allows machines to interact with their environments by creating actions, detecting errors, and offering rewards. It consists of a decision maker or agent, a set of actions, and the environment itself, with the goal of having the agent make better choices over time.

With machine learning, vast amounts of data can be analyzed. It can be used to deliver fast, actionable results, but in some cases, training requires additional effort and time. A combination of cognitive technologies, AI and machine learning can streamline the processing of information.

Why Machine Learning Matters

Experts believe that artificial intelligence will shape our future, and that anyone who can’t keep up with technological advances will gradually be left behind. The field has grown exponentially within the past few years simply because so much data is available and it’s become cheaper to store and process it. With machine learning, it’s possible to study complex data and use it to achieve faster and better results.

Machine Learning is Changing the World—And We Must Change With It

Machine learning is giving us the opportunity to go beyond a basic understanding of AI. With it, we’re finding out about machines’ learning abilities, biases, failures, and successes. Much like we’d learn psychology to see how the mind develops, we’re using machine learning technology to discover how computer systems work. These advances are changing the world for the better, and it’s up to us to use the technology responsibly.