Have you ever heard of machine learning? Well, this is an ability of artificial intelligence (AI) that gives systems the capacity to learn from examples and experience without obvious coded programming automatically. It focuses on the improvement of computer programs to collect data, and apply a training model to learn automatically.
The learning process starts with data that gives instructions, observation of examples, experiences and then observing patterns in information to make better decisions or choices in the future, centered on the examples provided. The key purpose is to let the computer program learn by itself without human assistance or involvement and consequently modify actions.
There are so many offers of mobile apps in today’s market. This has made the demand and development of mobile apps to go high. With the many apps in the market, how would your app stand out? The contemporary world of apps has made people want a personalized experience. It’s not just enough to create a good app; you must look for ways for the users to continue using the app. Machine learning and artificial intelligence can perfectly do the job for you. For example, it can find defects in human’s DNA which is thoroughly described in the article written by Google Cloud and The App Solutions experts.
Implementing Machine Learning into Modern Mobile Applications
So, how can you implement machine learning into a mobile application? We’ll start by looking at some of the mobile apps that used machine learning to improve their users’ experience and then go through a few ideas of machine learning applications that can be explored.
Snap Chat
Snap chat’s facial filters use machine learning and augmented reality to modify your face to your liking when you take a selfie. For instance, the flower crown on Snapchat detects your face and locates facial features like the nose, eyes, lips, and ears then uses patterns of a model facial shape to modify your face shape, add animations, and other accessories that you like.
Google Maps
People are using Google maps to find parking spaces. How incredible is that! But how can machine learning tell you where to park? Simply through data analysis. Google collected numerous location data and created models to alert users of available parking slots when they reach their destinations. This is made easier through the directions card which has a ‘find parking’ tag. It then gives you a list of available parking spaces near you.
Oval Money
We all know how saving can be difficult. With Oval Money, saving has been made easier. This is a financial app that uses machine learning by analyzing your previous habits on financial transactions and expenditures and offers a variety of easy options to help you avoid extra and unnecessary spending.
Tinder
A lot of people do online dating and searches for soulmates. Tinder is among the apps that people use for dating. It’s however different as it uses machine learning to find your perfect match. Tinder actually filters your photos to let the most popular ones appear first. Through its Smart Photo feature, it increases a person’s chances of finding a partner.
Netflix
How does Netflix know what you want to watch? Through machine learning and algorithm that personalize movie recommendations. The movies are categorized by year, actors, genre, length, reviews and other classifications. It uses your reviews on watched TV series or movies and recommends movies of the same genre since it knows the kind of movies or TV series that you like.
Mobile Apps and AI: Even More Ideas
These are just examples of popular mobile apps that use machine learning to create better user experiences. You can also consider using the applications for the following ideas:
Financial apps: Machine learning can play a significant role in giving financial advice by analyzing expenses and giving viable financial solutions.
Food apps: Machine learning can work on food apps to take food orders, suggest recipes and respond to questions on menu items. Based on your previous orders, the app can recommend foods that the user may like.
Transportation apps: Estimated arrival time for cab services, the cost depending on distance, and your driver’s information can all be provided through machine learning.
Other apps that can use machine learning to improve user experience include sports apps, time management apps, weather forecasting apps, and travel apps.
You can see how important machine learning can be to create successful mobile apps. With the many apps available for download, giving your users an enjoyable and convenient experience is paramount to have the edge over other apps. Let this information motivate you as you think of brilliant ways that machine learning can enhance mobile applications.
