Top 10 Machine Learning-Based Mobile Apps
- By Joshua Ahorro
- Mobile Apps
The smartphone market is the most active and the most dynamic demographic that the world has seen in a long time. For savvy businesses, smartphone users are a market that keeps on giving, as the world becomes more and more connected every day.
With smartphone use, the prevalence of app use has also emerged. People use them every day. With at least 1 billion smartphone users, the market is primed for the taking. E-commerce within apps, especially mobile games have stepped up their game with in-app purchases, while lifestyle apps follow the trend.
But for business owners, artificial intelligence (AI) is where it’s at, at the moment. Machine learning is going to be the next big thing in the smartphone industry. Manufacturers like Apple and Android OEMs are heavily investing in the technology, so you might as well jump the gun and start discussing your options. Here are the top 10 learning-based mobile apps today, for reference:
An app specifically targeted for scientists, especially botanists, the machine learning in this app is quite straightforward. It can identify types of leaves from images taken directly from the camera or downloaded to the gallery.
Maybe one of the most effective ways of incorporating machine learning in an app, Shazam is popular because it helps people identify a song through just the lyrics. It analyzes the songs people are listening to and read their lyrics to identify what song is being played.
It’s not commonly known that Spotify uses machine learning to make personalized music selections for its subscribers. Most music streaming apps are guilty of this, even Apple Music.
The same way that Spotify learns what songs and genre you like, Netflix uses machine learning and algorithm from the movies and shows you’ve to watch previously to recommend you something similar to interest.
Dango is an app that helps you choose the right emoji through what you type on your keyboard. It uses deep learning, a type of machine learning that allows the machine to read into your messages.
Yes, your favorite Apple assistant uses algorithms and machine learning to know what you’ll be asking on what time of the day, etc. Google Assistant and Cortana do this as well. The difference is Siri keeps it on the phone, while the other two do not.
Everyone’s favorite text-predicting app takes it to the next level by adding in neural networks to make its predictions more accurate and contextually correct.
While it’s blatantly obvious, Facebook’s use of artificial intelligence is bordering on creepy, and it’s one of the reasons for starting conversations within the relationship of machine learning and privacy.
Undoubtedly the best photo storage app right now, Google Photos is one shining example of how machine learning and algorithm can make a user’s life easier. Classifying photos, collating them and making presentations out of it? Impressive.
This might be a bit of a shock - but Snapchat heavily uses machine learning in the most unexpected place - on its filters. That fun dog face picture? It won’t be possible without the use of machine learning.
Machine learning is certainly upon us. If you have a smartphone, there is a big possibility that you are using an app with embedded machine learning capabilities. You may be reading this article using one right now.