Big Data has become the trending buzzword and also some of the other emerging technologies like Artificial intelligence and Machine learning are speeding up. From big data to deep learning techniques, many new technologies have made their way to different industry verticals which include the field of mobile app development as well. In this article, we will be shedding some light on the different roles played by machine learning – one of them is to develop wireframes for mobile app development. The good thing about machine learning apps is that they are endless virtually which leaves a great scope of use cases to get explored. As we can see from the above-given study report, 57 percent of the total consumers are willing to share their data with other brands and companies who are planning to use their data and make their user experience more pleasant. Now let us move straight towards the part where we will be sharing everything you need to know about how to utilize machine learning tools for developing the mobile app wireframes effectively. Use of ML to build Wireframes for Mobile Apps In current times, the smartphone plays a vital role for tech-savvy developers and budding entrepreneurs from across the globe who are working hard to build a cutting-edge mobile application in order to succeed in the market. But there are some professionals who have expertise when it comes to leveraging contemporary technologies like ML (Machine Learning) tools. Below are the fewer steps which are required for developing wireframes by using ML in mobile app development along with other technologies like big data. Step #1: Begin with the Pre-Planning and Research When dealing with the machine learning app development, it is always a better option to begin by pre-planning regarding the procedure once the research and development are completed. This step is vital and cannot be taken lightly in order to make sure that you can perform in-depth research and put more emphasis on significant conceptualizing before jumping off to another step. Being a mobile app developer, you need to ask a few questions to yourself which are taken into consideration for your pre-planning: • Who is the target audience of your application? • Is your application free or paid? • What are the main objectives of the application? If you answer all of these questions clearly then it will help you not only to simplify the entire process but clarify the upcoming steps of the procedure by using machine learning in mobile apps. Step #2: Design a Rough Prototype This is the next step where you need to perform rough and mental prototyping for your application where a mobile app developer can initiate after completing the discovery stage. In this approach, you need to take step by step measures to consider building for the app development project. This is the phase where you actually need to perform an entire psychological prototype of your mobile app which can help you visualize the original idea you’re working on. The mobile app developer can do such type of rough sketches to make the process easy to understand. Then the developer needs to find the usability issues which are faced by the app users and to overcome this you can go ahead and gather the feedback from the app testing team. Once you have exposed all the loopholes, you can now begin working to eliminate them and recheck the app for any issues. Step #3: Get to Know All Technical Possibilities To have a full comprehension of the visuals is not sufficient if you do not know the coding and wireframes behind your mobile applications. So, if you are the same who do not know the coding or machine learning algorithms for developing wireframes than you better need to understand the technical possibilities of your mobile apps first. Here, in this step, you need to make sure that the back-end machine learning app development can also support your application’s functionality efficiently and effectively. At this stage, you have to make sure that the notion of your mobile app is entirely possible and for that, you have to gain access to its public data which can be only done with the help of APIs. Also, know the exact stage that you’re choosing to develop your app, for instance, Android or iOS. Step #4: Testing, Testing, and Testing Once you have designed and developed your mobile app, the very next thing you are expected to test it by using machine learning tools in mobile apps. So, go ahead and figure out all the technical possibility which makes a prototype for your application which will help you in building a basic framework for the final outcomes of your application that will be visible to your end-users. Besides this, ensure to deploy your app by testing it a couple of times and resolving the issues which are surfaced during this stage to make the application more appealing for the target audience. Step #5: Gather Constant Feedbacks It is very crucial for your mobile app to continuously collect data from the end-users and optimize the machine learning algorithms to upgrade your mobile application up to its full user-friendliness. The app developers should get safer by designing an actionable plan for their data and collect all the data that the application users are sharing consciously. Focusing more on collecting data from customers will engage them more with your apps and understand the user behavior by improving the User Experience of your system as well. You can also get some better insights by in-depth research on your customer behavior with the help of demographics and analytics. You need to be patient as it can consume more time when optimizing your app, but the payoffs will also be extra amazing. Wrapping up! ML is gaining high values in mobile app development as it can help you to create high-quality wireframes. By following these steps, you can launch and deploy your app. Make sure that your application is checked thoroughly to prevent any issues from being displayed on your page. Keep Learning!