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One of the industries that benefit from machine learning the most is mobile application development. The use of machine learning became so widely spread that you might not even suspect that an app relies on it.

Machine learning algorithms find patterns in massive amounts of data to make data-based predictions and decisions. The more data ML processes, the better algorithms become and the more accurate predictions and decisions they make.

Today, three main types of machine learning are defined:

• Supervised machine learning – the algorithm is trained with predefined training examples. It is used for the ML to learn how to reach the right conclusions when new data is fed to it.
• Unsupervised machine learning – the algorithm is trained on data without predefined rules. It must find patterns and relationships to make predictions in the future.
• Reinforced machine learning – machine learning is trained to make a sequence of decisions. The agent learns how to achieve the goal in an uncertain and potentially complex environment.

Industries That Can Benefit From Machine Learning Application Development

Machine learning is the solution that is gradually finding its way into various industries. Use cases are numerous and, in this part, we are going to talk about the industries and spheres where machine learning can bring the highest value.

• Transportation

Smart and self-driving cars have already entered our lives. Artificial intelligence enforced with machine learning algorithms are used to monitor the traffic and predict changes. The combination of these technologies allows for cars to drive without human assistance.

• Healthcare

Machine learning is accelerating the healthcare industry. Such solutions collect and analyze patient data to diagnose and advise possible ways for treatment. Predictive healthcare is gaining traction.

• Finance

The finance industry has a huge amount of data that needs to be analyzed to make predictions for future data collection, management, investment, and transactions. Machine learning and artificial intelligence are used in the industry for fraud detection and fraud prediction.

• Cybersecurity

The technology can analyze data about incident reports, alerts, and more to identify potential threats and improve security analysis or even advise response.

• Manufacturing

Companies with assembly lines can use ML algorithms together with sensors and artificial intelligence to predict the need for maintenance. Thanks to their use, companies can avoid unplanned downtown and drops in production.

• eCommerce

The eCommerce industry already benefits from this technology. Personalized product recommendations increase the average order value and revenue.

• Marketing

This technology can be applied in the ads industry to improve the efficiency of ad campaigns by targeting users with highly personalized ads tailored to their specific interests and needs.

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