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Flutter is a platform where a lot of apps are building these days. Machine learning is a great concept where there are multiple fields that can be explored. Flutter works on machine learning and apps make use of it very effectively. Flutter is an undertaking of Google that works in collaboration with its own MLKit.
Machine learning in Flutter is promoted especially for the developers in the smartphone and tablet segment. Let’s understand how this entire thing works in depth:
Flutter - Build your apps easily
It’s a platform provided from Google that helps the developers in creating the apps for both the platforms, ie, Android and iOS. The developer will have to write the code once and the framework will implement it on both them. The platform also lets the developers create interactive widgets and attractive interfaces. The apps are also capable of working on a web-based system that can be accessed on any browser.
A smartphone should be able to use multiple sources in order to perform tasks better and provide you better overall user experience. Google keeps working on enhancing the consumer experience and in the process, provides better tools to the developers to do so. There are many aspects when it comes to how machine learning works.
There are multiple APIs that are present on the Firebase MLKit platform which can be implemented directly. Some features and key points are:
Machine learning techniques like facial recognition, text recognition, barcode, scene detection, etc. are present in the form of readymade APIs. You will have to go to libraries to find the suited one for the purpose.
If you have built your own machine learning, it will not be like that you can’t use it in the app. You are able to upload the model in the framework. Firebase will host it like any other pre-registered module.
Offline and Online
The framework provides the features to be used either cloud-based or even on-device. The on-device usage scenarios can be facial recognition and text recognition of any document or board.
Here, in this paper, we are going to explain the different aspects that the machine learning kit provided by Google is able to do.
The commonly used API is text recognition from the documents and boards. What it will do is it will take out the text from the document or the image and then you can copy the text and use it anywhere. You can also use the API to work on the device without using the internet.
This app is used by multiple camera beautification apps that detect the details of the face. It adds customized beauty features to eyes, cheeks, nose, and/or ears. The API can be used to add beards and other make-up add-ons to offer beauty features. The API will also be used in adding a security feature like unlocking the phone using face unlock.
Barcode scanning is also a feature that is used significantly by many companies. This feature is able to feed the virtual world the information from the real world that can be encoded in the form of strips and bars. The most common use scenarios can be encoding the Wi-Fi credentials so that people can connect to a public network.
Detecting an image
This API generally works over the internet. When the camera sees any object, it will try to detect using the image database that is connected to Google. For example, you are confused about a food item; you can open the camera and find the name. API will look for similar images in Google’s database. You can hire Flutter developers to build the app for you, which are integrated with these APIs.
You are in a new city and are unable to read the language. This API will help you in detecting the language and you can also integrate it with the translate feature. The user will be able to know the language and also translate the content in its native language.
The feature comes to its best use scenario when you are in a class or a meeting. The API lets users turn the speech into text in real-time. Users can also search by entering the words used in the speech to go directly to that part of the file.
The API is also used widely in the banking and financial services sector. Machine learning is capable of predicting the closure time of a bank account by analyzing the spending pattern of the customer. There are multiple other applications as well and financial institutions are able to take smart decisions. The machine learning kit in Flutter contains very intuitive and developer-friendly libraries that are able to provide some great results.
Popular Examples of Machine Learning
The only way to make someone understand or have a better understanding of a particular project yourself is to go through the examples that are already there and working successfully on the same module. We all use machine learning apps built under Flutter development on a daily basis and here are a few of the examples.
The app works in collaboration with Google Assistant. You will have to only open the camera and point it towards the object you want to learn about. Using machine learning, Google will try to differentiate between the text and object and provide the related details.
The Lens will be used to execute many tasks like saving a contact or copying an e-mail address. Thanks to machine learning you can find the same type of dress or search for a product.
It is seen multiple times that when you searched for a product but didn’t buy, you end up seeing multiple ads on other websites. This technique is used using the algorithms to encourage users to buy the product. These days, it is one of the most used examples of Firebase and Machine Learning.
A cloud-based backup service introduced by Google turned out to be a great tool in organizing the images and videos. The app is able to reorganize the pictures according to faces and places along with dates. The app also allows you to backup the unlimited images in HQ without any limits.
The applications of machine learning are getting wider each day. From building apps that use it to provide users to enhance their productivity to giving appropriate data to the self-driving cars. The working of this tech is basically in collaboration with artificial intelligence and algorithms used, in this case, by Google.
This is the high time when the management starts understanding the importance of machine learning and implements it in their organizations. The Internet has provided us the opportunity of having massive data for free. Machine learning uses that data to provide the consumer with a better result and increased productivity. Google is always working towards better user experience and consumer-friendly products.
Other than that, Flutter is a platform that is highly capable of providing better apps. These apps are integrated with different APIs that provide users a lot of different options. Features like text and face recognition, speech recognition, barcode scanning, etc. are only possible due to machine learning.