5 Mobile App Ideas That Uses Machine Learning

With mobile phones become a common accessory in every person’s life, it is safe to say that the market has grown tremendously in the past decade or so. Just like how mobiles hardware has become powerful, the software technology powering it has improved leaps and bound. One technology that we are going to talk about is machine learning. Machine learning is the part of artificial intelligence that focuses on self-learning with the help of data.

Mobile apps also use machine learning to make them more effective and offer more personalized user experience. When it is combined with the cloud and data-based tools, the experience can change.

In this article, we will be listing five mobile app ideas that use machine learning. By going through the list, you will be able to understand how machine learning can impact mobile experience and also equip yourself with the knowledge on which apps you can use machine learning. So, without any delay, let’s get started.

5 Mobile App Ideas That Uses Machine Learning

Intelligent Photos(IntelliP)

Phones and photos go hand-by-hand. There is no doubt that users want their photos to be organized and feel natural. This is where machine learning or specifically IntelliP can help. IntelliP is an on-device detection or recognition model that classifies images into multiple categories. The categorization is done based on the photos and is done continuously in the background when a new photo is taken or downloaded.

Apart from usability, the app developer can gain profound insight about the users itself, and that can help them further improve their mobile app ideas.


GeoInterest is an interesting mobile app idea that focuses on learning about the user’s navigation habits and help them in the process. So, what do a GeoInterest app will do? It detects the information regarding the place which can interest you. It determines it based on your past journeys. For example, it will take actions such as bookmark, store details and so on.


Journalism requires journalists to be present in critical situations to gather information. After all, it is a challenging job. This also requires creating reports based on the evidence present on a scene and talking to multiple people. But, it is not possible as not everyone might want to talk or share information.

Mobile-based correspondence is far better in this regard, and this is where the machine learning comes in. It can provide a near-natural experience and ensure that the necessary information can be captured. The extended journalism acts will interact with users in voice conversation and auto-generate a report. The report then can be reviewed by the journalist. That’s not all; there are more AI opportunities in Journalism. You can read more about it here.


You can also create map-related mobile apps that utilize machine learning. Maps are handy when it comes to navigation. You can use machine learning and learn from the data collected from thousands of users. This way, the app can help users with information such as the time it would take to find parking or where they have the best chances to get a parking spot.

There are other ways you can approach maps-related mobile app creation.

Emoji Prediction

Emojis are part of our online culture. They offer the user a way to share their emotion in the right way. However, adding them during texting can be a tough proposition. However, with machine learning and prediction, the use of emojis can be improved in a much better way. You can create a mobile app that lets you predict emojis based on what the user’s input. For example, if the user is typing a joke, the related emojis will be suggested to the user. This improves interaction fluidity and user experience. Many keyboard apps already use this mobile app idea for mobile.


This leads us to the end of the five mobile app ideas that uses machine learning. These use-cases will help you better understand how machine learning can improve the user experience. So, which mobile app idea did you like the most? Comment below and let us know. We are listening!