Machine Learning: An Integral feature of Mobile Apps

Updated 31 December 2020

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If we’re talking about mobile apps, then we cannot miss out on the Machine Learning applications.

In this time and age Machine Learning has become a dominant segment of the mobile app development industry, and has given significant profits to businesses.

The reason being, ML implements the AI operations and its algorithms are efficient enough to follow learning mechanisms to offer a better user experience.

Usability of Machine Learning Apps

Mobikul Mobile App builder implements the ML Kit’s ready to use API in Google’s Firebase.

This in turn instigates the application to respond swiftly, making it comparatively efficient.

Mobikul Mobile App builder supports two cases as of now, namely, Text Detection and Product Detection.

 

Moreover, the feature listing may be extended further. It includes landmark detection/ face recognition and barcode scanning for implementing uncountable use cases.

To know more – https://mobikul.com/features/e-commerce-mobile-app-machine-learning/

We generally use the ML Kit for Android whereas we use Core ML for iOS.

Beneficiary Factors: of the Machine Learning Apps

ML has become a core element and the reasons are very obvious. It has taken mobile app development to another level and that’s why has become the need of the hour.

Let us take a quick tour of Machine Learning benefits-

Usability of Machine Learning Apps

Scope of Machine Learning Apps

Machine Learning is the new language of digital evolution. One cannot deny the fact that our future world completely relies on Machine Learning technology.

Moreover, the future vision associated with Machine Learning is extremely vast. It has given the power to machines to discover and examine videos, images, graphics, etc.

Meanwhile, the advancement in Artificial Intelligence and Machine Learning has made it possible to acquire many future goals associated with technological advancement.

The scope of Machine Learning is not confined to the investment sector. It has spread its wings to various horizons such as information technology, media, entertainment, gaming, and the automotive industry, banking and finance, etc.

Considering the scope of Machine Learning, let us move forth and explore future opportunities that accompany the essence of Machine Learning.

Automotive Industry

One of the prime areas that relate to Machine Learning is the Automotive Industry. As digital evolution is at its upsurge, even the car manufacturer or automotive companies are revamping the conventional techniques and acquiring fresh opportunities to utilize the potency of data.

Innovation is the word and automotive companies are continuously acquiring various ways and means to associate with data so as to progress with automotive innovations.

The reason is data science and machine learning have set up a competitive edge for automotive companies and car manufacturers.

We must have heard of names of a few automobile companies such as Tesla, Mercedes Benz, Nissan, etc. These companies have acquired majorly in Machine Learning so as to develop innovative designs and meet the customers’ expectations.

Robotics

With time Robotics has gained extreme popularity and has become one of the most interesting fields of study for researchers and even the commoners.

Who doesn’t know the name of the first programmable robot named Unimate?

Thereafter, another robot names Sophia was invented, which was the first AI-robot of the 21st century.

What do you think made such inventions possible? None other than Artificial Intelligence and Machine Learning.

Not only this, robotics have reached that extent of development where researchers are experimenting and trying to develop robots that counterfeit the human brain. This is something incredible! isn’t it?

Such an invention implements technologies such as neural networks, AI, ML, etc.

Hence, Machine Learning and AI systems ensure us to provide robots that are human-like, in work and behavior, both.

Quantum Computing

Machine Learning is still at its initial stage. There more to it and we must wait to have a glance at what’s in store for us!

Quantum computing is one of them. I am sure most of us heard the term “Quantum” in physics. It is a computing technique that incorporates quantum scenarios such as entanglement and superposition.

The superposition quantum scenario helps develop quantum systems that can display multiple states at the same time, and in the entanglement quantum computing scenario two different states can be associated with each other.

It helps in describing the correlation between the properties of a quantum system. It is not as easy as it seems.

Such systems are developed by integrating innovative quantum algorithms that process data at a swift speed which in turn enhances the processing potency of ML systems.

Computer Vision

We’ve mentioned earlier in this paragraph that Machine Learning has given the power to machines to discover and examine videos, images, graphics, etc. This is the essence of Computer Vision that helps machines to recognize images, videos, graphics, etc.

Computer Vision has proven to be one of the prime fields of Machine Learning and AI.

Hence, Machine Learning has brought a drastic change in the mobile app industry, especially in terms of better user experience, reliability, and security.

That’s all for Machine Learning: An Integral feature of Mobile Apps. If you still face any issues, feel free to add a ticket and let us know your views to make the module better at webkul.uvdesk.com.

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