The Applications of Machine Learning

The Applications of Machine Learning

Although it has drawbacks or limitations, the advantages of machine learning translate to numerous applications that collectively center on process improvements.

The General Applications of Machine Learning

1. Automation of Processes: One of the practical applications of machine learning involves the utilization of autonomous or self-learning computers and applications that can lead to process automation. Automation can have numerous commercial applications because it reduces human input or participation.

2. Improvement in Data Mining: Machine learning can not only automate the organization and processing of large volumes of data but also generate assumptions. Note that data mining involves finding patterns in large data sets while machine learning involves learning from and making assumptions from data.

3. Enhance Existing Machine Learning: Another general application of machine learning is self-improvement. A specific machine learning system can continuously improve if consistently fed with historical or training data.

Major Commercial Applications of Machine Learning

1. Intelligent Digital Assistance: Apps such as Siri from Apple and Google Now from Google use machine learning to process voice commands or typed inputs and generate recommendations and improve the user experience.

2. Search Engine: Providers of search engine services use algorithms to automate the scanning, categorization, and ranking of websites based on specified metrics, as well as deliver results from search entries to users.

3. Autonomous Driving: Because one of the general applications of machine learning involves the automation of processes, the technology has been used to allow automated navigation through roads with minimal human input.

4. Delivery of Contents: Electronic commerce websites such as Amazon, social networking sites such as Facebook and Twitter, streaming services such as Netflix, and online advertising delivery platforms use machine learning to deliver appropriate contents based on user preferences.

5. Safety and Security: Another application of machine learning involves the promotion of public and virtual security and safety. When continuously feed with training data, the system can discover patterns and provide assumptions about possible threats.

6. Health and Medicine: Researchers have investigated how machine learning can be used in improving medical processes. Some of their studies have used this technology to automate and expedite diagnosis procedures, reducing medication errors, and aiding with clinical research, among others.

7. Economics and Finance: Machine learning has also been tested for use in analyzing and making predictions about economic trends, as well as in the analyses of financial markets. The technology can be used to improve decision-making through the analysis of big data.

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