15Jan 2018

Machine Learning in Mobile Apps Development: How to Implement It in Your Apps?

Machine learning is the field of computer science in which the computers can learn on their own without the need to code and program for the different elements. In most of the cases, when you think of machine learning, you may think about the movie Terminator where the advanced robot from the future is self-learning and intends to kill. Now the question is, “is machine learning possible and by when can we expect machine learning in our lives?”. The answer to this question is machine learning is here and has become quite mainstream. You do not need to go far to experience it and just have to look at the smartphone in your hand. This small device makes use of machine learning and helps you in many ways. Many companies use it to provide better user experience to the users.

One another misconception in the minds of people and even in the most mobile app developers is that the machine learning is something that is quite complex and requires some rocket science to implement it in your apps. This can, therefore, be used by only the effluent organizations that can afford R&D departments.

However, this is not the case right now, and even the smaller companies can quite easily implement it in their apps and provide better user experience to the users.

Some major apps that use machine learning in their apps:

Machine learning has been used in many apps. Some of the most popular apps that make use of machine learning in their apps are as follows:

Google Play Store and Apple App Store:

Every Android smartphone user must have used it at some point in time to install the apps. Machine learning is widely implemented in the Google Play store as based on the types of apps installed and apps browsed on your device. They can provide suggestions on which apps the users can install and based on the recommendations the users can discover new apps and use it as per their liking. For example: Suppose you browse Facebook app, you are provided suggestions to install WhatsApp, Twitter, and other such apps.

Snapchat Filters:

Snapchat-filters

Snapchat is a popular social media app that helps to connect with different users. Many features are implemented into it to provide better results related to you and that you are interested in. Apart from that it also includes snapchat filters that make use of facial recognition to recognize the face and learn what the face looks like.

Siri, Cortana, and Google Assistant:

Voice assistant like Siri, Cortana, and Google Assistant also make use of the machine learning. Based on the user responses and their voice searches, these learn more and more about the users and then aim to provide relevant and accurate results. Apart from this, they also aim to learn about the different user voices and provide results based on the same.

Shopping sites:

E-commerce Store

Various E-commerce sites like Amazon aim to provide content that is similar to the user’s request. In this, if a user searches for a particular product, various related products can be displayed. This helps ensure that you can find out the relevant products based on your interests. Also based on the browsing history, you are presented with appropriate offers to help the users to carry on transactions. The users are also informed about the price drops for a particular product.

Provide relevant ads:

Ads are displayed on the mobiles to attract more and more consumers to a particular product. In order to enhance the click-through rate of the ads, machine learning is implemented. This displays the ads based on the user, their interests, and their behavior.

Tinder:

Tinder is a very popular dating app to help you provide the perfect match for your soulmate. It also makes use of machine learning with the help of smart photos to find a perfect match for the user. Based on the user response to the people on a particular picture, you are displayed with the most popular profiles first. This, in turn, provides better results and find your soulmate easily.

Netflix:

Netflix also makes use of the Machine Learning app like Linear regression, Logistic regression, and other machine learning algorithms. With the help of machine learning, you are recommended about the related movies so that you get a better user experience to the users. Here various films and serials are classified by genre, actors, reviews, length, year and then prioritized as per the machine learning algorithms. Based on the user’s responses as well other users are recommended the content.

How to implement the machine learning into your apps?

Now that we have seen many examples in which machine learning is used, it becomes necessary to know how to implement the machine learning into your app.

Tensor flow:

Tensorflow, an open source machine, learning library from Google can be used to implement machine learning into your apps. Using this, the apps can make use of some interesting elements with the help of data flow graphs for the numerical computation. One of the best parts of this is that it provides a flexible architecture to deploy one or more CPUs and GPUs in a computer, server, and mobile with the help of a single API. Users can conduct machine learning and neural network research. It is quite easy to implement on your website, and there are many resources available to help you to do so. Many multinational companies like Google, MI, Snapchat, Intel, Dropbox, Twitter, eBay, and many more such apps.

Core ML:

Core ML is the provided by Apple and can be used to create mobile apps and implement machine learning into the iOS apps. Various Apple elements like Siri, Camera, and QuickType can be used to make the most of these. Various aspects of machine learning can be quite easily implemented with quite a few lines of codes. You can quite amazing features like face detection, text recognition, object tracking, image registration, face tracking, image recognition, barcode detection and several such items. It also makes use of natural language processing with the help of certain features like language identification, tokenization, lemmatization, part of speech, and named entity recognition. Apart from these more than 30 deep learning layer types. Apart from these, you can also employ the CPU and GPU and enhance its performance.

Amazon Machine Learning:

Amazon Machine Learning is managed by Amazon and provides easy to manage tools to help implement machine learning into your websites. Even the beginners can quite easily implement this. It helps you to make use of the smart APIs and real-time predictions for different apps thereby providing better results for the users. One benefit of using Amazon machine learning is that it is highly scalable. This can help you to enhance resources as your business grows. Thus you have to pay only for the resources that you use.

Wit.ai:

Wit.ai is another platform that helps to implement machine learning into the web apps. With this, you can quite easily transform the apps and provide different solutions based on the natural language. You can also transform the user input in the form of various actions and transform it into different actions. You can also quite easily implement it into your website. It can be used for free both by the individuals and for commercial use.

Benefits of machine learning in the apps:

Machine Learning in Mobile Apps Development

Machine learning in the apps turns out to be quite helpful and beneficial. Here are some of the benefits that are provided by the machine learning.

Provide better and relevant content:

Providing the relevant content to the users turns out to be quite helpful to the users. When the content is provided to the users based on their interests, these get better responses from the users.

Increase sales:

Machine learning if properly implemented in the e-commerce websites, can help to enhance the sales of an organization. Based on the behavior of users, their browsing experience, their purchase history and other such parameters, appropriate projects can be suggested to influence the users to buy more products. Apart from these, you can also provide add-ons for the product.

Security:

Safety and security are also provided with the help of machine learning. With these, you can block certain IP addresses, users, and locations that indulge in malicious practices.

Predictions:

Machine learning with the help of loads of data can help to learn about various information about the users, their behavioral patterns, market, upcoming trends, and various other such information.

Provide better user experience:

Machine learning with the help of personalization and by offering better results can turn out to provide the better user experience.

Brand development:

The brand development is quite crucial, and many businesses aim to achieve it. The information gathered with the help of machine learning can be used to provide a better experience to the users by knowing more about them. This in turn then can be used to develop a brand name for yourself.

Summary:

Implementing machine learning into your apps is the need of the hour to provide better results to the users. It is because, in order to compete with the top apps, you need to implement the technologies implemented by these. This can also help you to provide you with an extra edge over the other apps and stand out from the other apps. Apart from these, these can also help you to provide better services to your users and turn out to be more useful for them.

Acodez is a leading mobile app development companyin India. It is known for its innovative methods in the app development. Latest methods of app development are put to use to make sure that your apps meet the needs of your users and provide the better user experience. This future preparatory approach to app development has helped us to develop some amazing apps for various prestigious companies.

 

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1 Comment

  1. rachana

    Informative article. Machine Learning improves user experience and maintains customer loyalty and retention through secure Authentication Process, easier and Faster browsing and supports Financial Application.

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