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Machine Learning App: How to Implement AI and ML Into Your App

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Machine Learning App: How to Implement AI and ML Into Your App

With AI learning the behavior and preferences of the user, you’re much more likely to make app sessions better and more memorable.

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In recent years, artificial intelligence, machine learning, and augmented reality have taken mobile app development by storm. When is it reasonable to build a machine learning app? With Apple and Google both encouraging developers to use these technologies — and making it easier to do so — businesses can vastly benefit by increasing user satisfaction and engagement by utilizing AI and ML.

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Are you wondering if you can implement AI for your business?

There are numerous uses for AI in web and mobile applications. The main goal is to implement a deep learning process into your app to recognize patterns and then apply these learnings to solve various complex queries. Here are the most common uses of AI and ML for businesses.

Learning User Habits

AI is great for dealing with complex data like analyzing preferences. Building products with user experience in mind is a priority for modern applications. Appealing visuals are not enough to keep your user base happy, but AI can help with that. While most people do not bother to customize or personalize their apps, small things like choosing which screen appears first or discovering what color theme is the most popular can make the user feel that the app is designed specifically for them. Apps in which the user has to go through many steps to complete a task can also easily use AI to make it faster or reduce the cognitive load on the user.

Recommendations

We already have AI recommending products or services to us on a daily basis (e.g. Netflix, Amazon) and this is all thanks to algorithms. Learning what a specific type of user (based on age, gender, location, previous purchases, etc.) usually buys is a good way to predict the best options for them without having to use annoying and badly targeted marketing. Knowing what someone’s preferences are helps to facilitate ease of use and keeps them engaged for a longer period of time.

This method works extremely well for entertainment apps or those that sell products, meaning we can guarantee that all new content will get to the right people.

machine learning app

Face Recognition

Current mobile devices are now able to use the complex data of a human face to recognize who a person is. The correct algorithm and a large enough selection of a person's pictures can provide a high degree of accuracy using this method. This can be used for both fun and security. Although locking a device with a fingerprint is currently more secure than 2D face recognition, as AI gets smarter and faster, 3D face recognition will be utilized by more applications to work along with, or replace completely, fingerprint scanners.

Making Everything Easier

The amount and sophistication of smart devices is constantly growing, controlling lights, and heating and air conditioning systems and refrigerators, to name but a few, but it can be a little bit of a hassle individually adjusting all these. Smart home products and systems can incorporate AI to work with the user and not just for the user. Our phones can become our personal assistants by setting optimal temperatures, turning lights off when we fall asleep or reminding us that we don’t have milk when we are shopping. Further, speech recognition allows us to learn applications quickly and interact with other devices around us more easily.

Mobile Camera

Computer vision is constantly improving, mostly thanks to machine learning. The most common combination of these two features are apps that recognize people, everyday objects like lamps, text, or even works of art. Everything from scanning barcodes to detecting facial expressions on photographs works faster and with more precision using machine learning. Camera applications can add filters to photographs and videos by detecting and tracking certain points. We can interact with phones via gestures because it learns and detects them. Every application using a camera can be better and more engaging for the user with computer vision.

machine learning applications

Summing Up

First impressions in app sessions are crucial for retaining new customers. With AI learning the behavior and preferences of the user, you’re much more likely to make these sessions better and more memorable.

All the data companies get from their customers is extremely valuable and should be used to not only improve the user experience but increase the chances of future business.

It is also worth noting that AI can be used to solve staffing problems where certain kinds of work can be fully or partially automated.

Consequently, progressive businesses are very quickly integrating AI into their mobile and web applications to create useful apps for their customers. As such, AI is a highly exciting and lucrative area to be involved in.

TrueSight is an AIOps platform, powered by machine learning and analytics, that elevates IT operations to address multi-cloud complexity and the speed of digital transformation.

Topics:
ai ,machine learning ,app development ,recommendations ,face recognition

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