Machine Learning is a form of Artificial Intelligence that enables a computer system to learn without being explicitly programmed. Machine learning sifts through data to look for specific patterns and uses there patterns to program actions accordingly. Machine Learning (ML) is quickly expanding and is growing in recognition owing to the fact that ML can play a key role in a wide range of critical applications, such as data mining, natural language processing, image recognition, and expert systems. ML provides potential solutions in all these domains and more, and is set to be a pillar of the future!
There exists two types of machine learning: Supervised and Unsupervised. Among the different types of ML tasks, a crucial distinction is drawn between supervised and unsupervised learning:
|Supervised Machine Learning||Unsupervised Machine Learning|
|The program is “trained” on a pre-defined set of “training examples”, which then facilitate its ability to reach an accurate conclusion when given new data.||Unsupervised Machine learning uses those type of algorithms that try to find correlations without any external input. The program is given data and must find patterns and relationships therein.|
Why Machine Learning?
- Machine Learning churns out high quality predictions/insights that are useful while making decisions without any human interference or intervention.
- Machine Learning digests large volumes of data that would otherwise take a lot of time and effort if done manually, interprets and then releases predictions or provide insights that are conducive to the productivity of the enterprise.
- In simpler terms, Machine Learning is one such tool that guarantees results that contribute towards the productivity of an organization.
Who’s using it?
- Financial Services
- Health Care
- Marketing & Sales
- Oil & Gas
Real world examples of Machine Learning:
- The self-driving Google car is an intelligent form of Machine Learning.
- Online recommendation offers such as those from Amazon and Netflix are Machine Learning applications for everyday life.
- Knowledge about your customer’s feedback on Twitter is Machine Learning combined with linguistic rule creation.
- Fraud detection is a form of Machine Learning used in Financial Services and the Government.
Machine Learning Process:
Feel free to contact SpadeWorx to introduce the benefits of Machine Learning into your business!
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