How to implement Machine learning in an Android app?

25Oct - by aiuniverse - 0 - In Machine Learning


As you already know-how Machine learning is playing a crucial role in predicting your upcoming actions. Now it’s time to see how Machine learning is revolutionizing Mobile app development.

What is Machine learning?

Machine learning is the application of Artificial Intelligence which makes computers predict the outcomes automatically without the intervention of human beings.


Commonly three types of Machine learning algorithms are available:

A supervised Machine Learning algorithm

In Supervised Machine learning, you are having both input and output variable and then the algorithm is used there in order to predict the output variable.

Unsupervised Machine Learning

In unsupervised machine learning, only the input variable is available instead of an output variable. In Unsupervised Machine learning, data is divided into groups in order to get more information.

As per the research conducted by bcc research, the global machine learning market totaled $1.4 billion in 2017 and is estimated to reach $8.8 billion by 2022. Machine learning vs Artificial intelligence also a most debated topic for data analysts.

Le’s have a look at some of the top machine learning applications


One of the most famous examples of Machine learning mobile app is Netflix. And in the present age, everyone is aware of that.

The reason behind this is that you want to watch each and everything before the time you think.

This is not magic, but if we talk about some years ago, this might be considered as magic. But this is not at all magic and the ruth behind this is just a Machine learning.

Netflix has covered its journey from a DVD rental website to a global streaming service. And this has become possible only with the help of Machine learning.

Various Machine learning algorithms are used in Netflix such as Linear regression, Logistic regression. These algorithms of Machine learning help Netflix to suggest personalized recommendations.

Netflix’s content is classified by genre, actors, reviews, length, year and more. All these data go into machine learning algorithms.


Every youngster is aware of this word Tinder that it is a dating app that helps in finding a soulmate. Tinder helps in finding a perfect match and this becomes possible only with the help of Machine learning. See how

Machine learning helps in making smart photos of the users which increases the chances of finding a true and perfect match. Tinder uses all kinds of love spells and potions, and one of them is machine learning.

But how is it possible?

Machine learning in tinder helps in showing a random order of your profile photos to people and analyzes how often they’re swiped right or left. With the help of this knowledge, it allows Tinder to manage your profile and put the most popular photos on the top of the profile. With the passage of time, it helps constantly in improving your profile better and better.

And finally, you’ll get better results and find your soulmate in no time.


This is one of the most popular platforms where machine learning is playing its important role by giving recommendations to the users.

There could be seen a fantastic combination of augmented reality and machine learning algorithms in Snapchat for the computer versions.

So how do Snapchat filters work?

First of all, Snapchat detects a face. Then the software sees a photo as a set of data for analyzing each part of the face. But the query is that, How does it become possible for the Snapchat to determine which part of the image is facing?

Well, the software analyzes this difference by looking and between the dark and the light pars of the image individually. The software goes on scanning the photo again and again and it helps the software to detect the difference between grayscale pixel values underneath the white boxes and the black boxes and finally, this helps in detecting which part of the image is a face.

Let’s take an example, we can detect the shape of the face by keeping in consideration these facts: the bridge of the nose is usually lighter than the surrounding area on both sides, the eye sockets are darker than the forehead, and the middle of the forehead is lighter than its sides. This type of algorithm will not work in the case if you tilt the face slightly but it’s really accurate for the front face.

Face recognition Snapchat

Apart from detecting a simple face, if you want to apply a crown in the Snapchat, the app needs to do more than detect a face. There is a need for locating facial features.

Final words

So, these are some of the mobile applications where machine learning is playing an important role. The above-given examples could properly meet you with the importance of Machine learning in Mobile application development.

So, if you are also looking for developing Machine learning-based apps, then hire Python developers who can make such kinds of apps comfortably.

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