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Scope of Machine Learning

Scope of Machine Learning (ML) is vast, and in the near future, it will deepen its reach into various fields like medical, finance, social media, facial and voice recognition, online fraud detection, and biometrics. Gartner predicts that 30% of Government and large enterprise contracts will require AI-fueled solutions by 2025.
Cyber security is another area where we will see huge adoption of ML, which aids multi-layer protection. ML shall also fuel areas that are highly dependent on data.
For example, in marketing, Machine learning can analyse data and evaluate it for better results. Similarly, in the education field, institutes and colleges can use predictive analytics to recognise patterns in students and assess their abilities. Let’s understand the scope of machine learning in the future in various fields:

Medical:

Machine learning and AI go hand in hand. In the healthcare sector, machine learning is doing wonders by helping doctors in making clinical decisions. ML creates better insights to make better healthcare decisions. By integrating ML and AI technologies, the healthcare ecosystem is benefitting in multiple areas such as task automation, data analysis, and predictive analytics and maintaining health data on the cloud. This, in turn, is saving a lot of time and money. Robots have been used in hospitals to provide assistance, and the results are surprisingly overwhelming.

Cybersecurity:

Machine learning is critical in the cyber security space. Why? There are many reasons. ML can analyse patterns in the past and help to prevent similar attacks, thus, helping security teams to be way ahead in preventing attacks. Moreover, it reduces a huge amount of time in routine tasks.

Digital voice assistants:

Voice assistants are high in demand, and this trend will surge in coming years too. It is predicted that one in every eight people in the US uses a smart speaker. Siri, Google Assistant, and Alexa are a few popular ones. We have seen a drastic improvement in these assistants over the years, where they are now able to solve problems rather than just introducing the product. Today, you can make a meaningful conversation with Alexa in a far more natural way as compared to earlier. Machine learning will help in streamlining meaningful conversations. There would be more and more smart devices out in the market with security as the key focus area.

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