Now is the age of AI or Artificial Intelligence. Without even realizing it, AI is being used by us either directly or indirectly. Today, the age has arrived where we require the machines to help us and assistance. Mobile App Machine Learning or ML is one of the most widely used applications of Artificial Intelligence solutions.
Machine Learning is referred to the technology where ‘Cognition’, which is very similar to the human brain is used in the form of software, application and devices. As stated earlier, AI is being widely used by the AI development company that brings to public use some great services.
List Of Mobile Apps Where You Can Apply Machine Learning Techniques
Let us take a look at some of the best-known applications where AI is used:
1) Netflix
This particular machine learning is one of the most widely used apps in today’s world. Little did we know that a simple DVD rental website would turn into such a streaming service worldwide. Machine learning software such as Linear regression and Logistic regressions to name a few are utilized to better understand a user at Netflix.
Ever wondered how the App offers you recommendations? How you receive alerts and updates? Well, you have the Machine Learning technology to thank to. Data such as reviews, actors, genre are used by the Machine learning abilities of the App to know the pattern of a user’s tastes and choices.
2) Tinder
Tinder is the ‘Cupid’ from the Tech-world. It is a Cool mobile App which is used to get you your perfect match. And you thought there was some kind of magic going on, on your mobile phone? Well, not exactly.
All that Tinder does is to apply Machine learning to ‘arrange’ as per order as to how many times your profile has been swiped left or right in order to finally suggest you a match.
Intelligent isn’t it? Well, that’s Artificial Intelligence actually. This system gets better with the input that is provided, in other words the more you use the App, the more efficient it becomes.
3) Oval Money
Who would have thought that you could have your ‘personal accountant’ right on your phone? Well, now you have it in the form of Oval Money.
This is an all-cool mobile App which utilizes the knowledge of your expenses done online through the technology of Machine Learning to offer you better ‘saving’ suggestions. This is done by gathering data by analyzing the transactions done by you. So, now you have the AI to help you shape-up your expenses as well.
4) SnapChat
This is yet another fun mobile App which has been developed using some great features of Machine Learning and a whole lot of Artificial Intelligence. Here, the ‘Augmented Reality’ is used in combination with Machine Learning.
The App detects the face pattern of the user repeated scanning techniques. The algorithms are used to locate the facial features, scales it and rotates it accordingly.
The Pixel data is used to analyze the brightness and darkness of each point. Now a ‘mesh’ is created which represents a 3D mask that can move as the video data comes in for various frames.
Now, the ‘mask’ or the mesh is deformed and accessorized accordingly to give you the final results. This app is a wonderful revenue opportunity, as various brands advertise here.
5) Google Maps
Google maps has grown in it popularity in recent times due to sheer resourcefulness. This mobile app is so convenient that it also helps the user find an appropriate parking spot for their cars.
This is once again done through a combination of Machine learning and data analysis. Various anonymous aggregated information is collected to finally be able to assist the user in the future, through the location data.
The standard logistic regressions is utilized to spot the parking locations and assist the driver accordingly.There are a lot of leading mobile app development companies which offers cutting edge services in this field.
The companies have a well-experienced team and a long trail of success under its belt to boast of. For development, a React Native App Development Company who offer a wide range of development services should be hired.
Places Where Machine Learning Can Be Easily Implemented
While these are some of the mobile apps already in use, let us take a look at some of the places where the Machine learning can be easily implemented.
1) E-commerce and Machine Learning
This can be used to help you with recommendations regarding fashion, trends, sales information. Accordingly, the required information and recommendations can be provided to the users.
2) For Sports Forecasting
Yes, in the near future the outcome of a certain sports game can easily be predicted with much accuracy. This is easily done through a machine learning model written rights.
3) Healthcare Apps
This one is a sure success. Here the Machine learning technology can be used to give advice to the users based on their symptoms. This technology can also predict the possibility of an upcoming ailment and also give solutions accordingly.
4) Food App
This mobile App utilizes collective data to offer recipe ideas and much more. Now, the app can ask and answer questions and also order food for you as per your tastes.
With the previously collected data, the ML can offer you new recommendations on the menu or places to eat. It can also analyze the delivery time for your order which is based on real-time traffic conditions.
5) The Time Management App
This Machine learning App is sure to be popular in the near future. The time management app will help the user to better schedule their tasks, time their work accordingly, so as to best utilize the time. It also helps you make a priority list for your work for the day and also makes the ‘to-do’ list for you.
Conclusion
In order to deliver such magical Apps in the future, we can hire a perfect AI development company that offers Artificial intelligence solutions. Let us take a look at one of the leading companies:
There are available various Hybrid App Development Company services that offer hybrid application development solutions along with advanced mobile frameworks. Basically, both the native apps and web applications are combined under this technology.
