The machine learning technology seems promising, and has the potential to bring a significant change in the tech world soon. It is a subcategory of the Artificial Intelligence research, and gaining prominence in the market these days.
ML is an epitome of a new software development era where desktops, and other gadgets don’t need any special coding to accomplish the tasks. In place of that, they diligently gathers and analyzes valuable insights required for drawing the apt conclusions.
Today, the machines can easily make the decisions by referring previous experiences. Note it, the learning process demands special algorithms that would instruct the machines. That’s why, the use of machine learning in the mobile app development has taken the spotlight.
Application Areas for Machine Learning
Being multidisciplinary in nature, the machine learning finds its implementation in a variety of field. Let’s have a glimpse at them:
Robotics
Taking a deep look into the robotics world, you’ll realize that the engineering involves both the mechanisms and cognitive technologies. Presently, we’ve witnessed that the robots are assisting people in their household and office work. And, the people are operating these machines through voice commands or with tool actions by tapping on their phone’s screen.
Data Mining
In the data mining sphere, a big amount of data is analyzed. This involves complete data storage and maintenance. The machine learning offers a tool set and the learning algorithms to figure out all the possible relationships.
Finance
Within the finance industry, the machine learning is basically used for the prediction of the future trends, bubbles, and crashes. For instance, to evaluate the credit ratings, the custom software can easily fetch all the relevant information about the borrowers like previous transaction history, social media activities, etc.
eCommerce
For the eCommerce industry, the machine learning has opened the door for a lot of opportunities. Be it in terms of increasing the business revenue or enhancing the customer service experience, the role of machine learning is wonderful.
eCommerce giants like Amazon uses machine learning for products suggestion to their clients. This suggestion system adjusts while you’re surfing for the products. If you click on the new pages constantly, then it will learn that you’re are not interested in that particular product, and soon recommending some other products. Furthermore, it not just learns from you but, also from the experience of the people residing in your neighborhood. All this contributes toward an enhanced personalized experience.
Given below are the best possible options for your eCommerce mobile app:
- Product Search – This is essentially the most prominent feature of a mobile app. The prime reason for this is the screen size of the mobile device. You can show only few products on the mobile screen, and the users are required to scroll down to see other products. The machine learning can make your mobile app to learn from the users search activities, so it can show up the most relevant products, and understands the typed query on its own.
- Product Promotion & Recommendation – The second most popular way to boost the business revenue is to provide the right promotions and complimentary items before and after making a purchase. You can easily see this on the famous eCommerce sites in the way “people who bought this also bought that”. This solution is provided on the basis of content analysis, buyers behaviour and their purchase style. Predictive analysis makes this process simpler, so your app recommendations will become relevant with every visit.
- Trend Forecasting – The machine learning is highly beneficial in accumulating the trends and sales information from the multiple sources (designer reports, social media, etc), and create a forecast in the real time. Not only that, you can even develop a system which adds new inventory automatically.
Healthcare
If you own a healthcare business, then we suggest you to use the machine learning. A lot of health tracking applications can evaluate your daily water intake and the number of activities performed in a single day. In case, you skip workout, or drink less amount of water for some days, then the app will inform you that it takes a toll on your health (if you continued to do it so for long).
Fitness Tracking
The mobile fitness apps help in monitoring the daily activities, number of steps, jogging rhythm, and a lot more. In the coming years, such kind of apps will assess the anonymous user data and offer effective suggestions to attain your goals as well as the diet/exercises to get faster results.
Best Machine Learning Tips for the App Developers
Putting more data to the algorithm can help you in reaping the accurate results and predictions. That implies, the machine learning app developers have to bid adieu to subsampling, and utilize all the available data properly.
The top factor for determining the project’s success is to opt for the most suitable ML method. Remember, the model’s simplicity ease out the learning process and renders the accurate predictions.
Involvement of the data scientist in the project can felicitate you in choosing the correct method and parameters for the splendid results.
ML is entirely based upon the data. The improper data collection can hamper the prediction potential.
Developing a solid knowledge on the data features and its improvements can bring a positive impact on both the learning process and predictability as well.
It is necessary to consider the business model and production capability of the clients at the time of creating the machine learning algorithms.
A proper rigorous testing is required for the machine learning algorithms, which should be given main preference while deciding the price and timings of the projects.
Final Words
With all these applications, it is clear that the machine learning has become the mainstream in the tech industry. Building a mobile application for your business by incorporating the ML algorithms can make you one step ahead in the growing industry. The shoppers are spending a great amount of time online by using their mobile devices, and want their shopping experience to be super-comfy. So, it would be great to deploy the machine learning in your mobile applications.
