Have you ever noticed that the post on Instagram, Facebook or on similar channels that show you the feeds that you have interacted the most? It can even be the pages you like or channels you visit on YouTube.
This is the application of Machine Learning!
So, what is Machine Learning?
Well, it is that domain of AI (Artificial Intelligence) that provides the ability to the computer to learn from the past experiences on its own and improve the experience without any human intervention.
In this, the computer learns from examples, direct experiences, data available and observations. It analyses the patterns, makes fantastic decisions and prepares itself for taking better decisions in the future.
But, why is machine learning going to be the next big thing?
If you are building an app that deals with posts or data coming from different sources such as posts from the pages or users, news from different media channels, listing of items on your e-commerce platform or different platforms like Instagram, Saavn and YouTube app, everything is now in great need of machine learning to improve the user experience as much as possible. After all, it’s the user’s experience that improves the user retention on your app.
If your e-commerce platform is built on the principles of machine learning then it can drive more customers than a platform build without it because if a customer’s gender is female and she is searching for a top from Zara and chooses the colour black then the system will automatically analyse and will show the branded quality top wear made for women in the colour black so that the user who is browsing through the app scrolls down for more results
Not only this, if you are building a social app or an app which has feeds from different channels then it shows you the contents based on how you interact with the app. For example, the Saavn app builds playlists for me according to the genre of the music I have recently played.
The same happens with the Flipkart app, it shows me the items to buy based on the items I have recently browsed.
Any domain, the machine learning is surely the next big thing.
What is the difference between the Machine Learning and Artificial Intelligence?
Artificial Intelligence (AI) is the broader concept where computers carry out tasks in the smartest manner using their own intelligence.
Machine Learning is an application of AI that provides the ability to the computer to learn from the past experiences and make better decisions to improve the user experience.
So, let me explain you this with a short story.
There was a colony of ants who used to follow a path - Left, straight, right and then straight because they learned by their past experiences keeping in mind that if they follow some other path then some poison might kill them. This is machine learning.
But one day someone displaces the poison and keeps it on the regular path of ants. What will happen if they follow the concept from their past experiences? They will die! But to think in the smartest manner using their own intelligence and change the path according to the presence of poison in the path is called Artificial Intelligence.
Is it more of a backend task? Why and how are mobile developers going to implement machine learning in their mobile applications?
No, it’s not a complete backend task. The backend developers can actually provide you the data but how to play with it, it depends on you. Not only this, what will you do if your app is offline? For example, the Google’s assistant can make a phone call even when there is no internet connectivity in your mobile phone or can set an alarm for you even when there is no SIM card in your mobile handset. Not only this, have you noticed your mobile phone’s camera detecting your face while taking the photo? This is the application of machine learning in a mobile application.
You can apply machine learning to your app using Firebase ML Kit which was launched by Google in I/O 2018. Firebase ML Kit is the best framework available according to me today. It is available for both Android and iOS platforms with minimal coding. It is for experienced machine learning developers and well as for freshers. And here lies it's beauty.
Currently, it is in BETA stage and provides support for common use cases such as barcode detection, text detection, face detection, landmark detection and labeling of images. But you can deploy your own models in Firebase using TensorFLow Lite and make your app work on your model. Not only this, you can even make use of Google Cloud Vision API and Neural Network API inside a single SDK of Firebase ML Kit. It’s API works on both on-device and on cloud.
Machine learning is surely the new era of computer programming and how you build an app. Today anyone can develop an app but how to make it work, will prove to be the difference in user retention on your mobile app and so it is the next big thing for the mobile app developers.
Stay tuned to this blog to check out the actual codes and implementation of Machine Learning (ML) in Android Applications.