Machine Learning (ML) is a subset of Artificial Intelligence and, it’s here to certainly bring a massive revolution in the world in the next few years. Experts of the industry believe that ML based practically useful solutions will soon be availed to general users via the mobile application development technology. Apps are way easier when compared with a program in a PC.
ML is triggering the beginning of the new era of software development. With the ML technology, developers would no longer require special programming for their computers, gadgets, and other devices aimed at accomplishing several tasks. These devices will collect and analyze the information that they need to draw appropriate conclusions and learn during program performance, instead.
Today, the ML technology already carries the experience from previously completed and implemented operations and makes decisions just we do. It happens through a special algorithm that makes machines capable of learning things on their own. The targeted devices will be mobiles and, the objectives will be achieved by the mobile app development.
In the beginning, ML was completely a PC-focused technology, but now, with the growing trends of mobile app development, it’s more shifting toward the mobile app development. It is what inspires almost all IT firms across the world starting to promote ML as the next big thing in the mobile app world.
Modern smartphones now come with sufficient power to handle and perform critical operations. Following points confirms this:
- The language software of Google uses the neural network and provides languages translations optimized for smartphones. It also supports devices without the internet.
- Lenovo is testing a new smartphone-tech that would perform many operations without an internet connection. Two best examples are indoor geo-location and augmented reality.
- During WWDC 16, Apple presented Siri SDK that allowed developers to incorporate this feature into their apps.
Areas where machines learning apps can be implemented
Machine learning mobile apps can be applied to a variety of areas that need the intersection of technologies, science and business.
Use of machine learning in robotics
The capabilities of ML can be used to aid robotics. We can easily spot a lot of manufacturing units have robotics installed in their product unit. We are also seeing the emergence of the age in which the robots can assist people in doing their works. These ML-enabled robotics can also be operated via voice command or from remote locations via a few taps on the screens of smartphones. All there required are the machine-learning capability for the correct performance, even in an unpredictable environment.
The ML Implementation in data mining
Modern day’s businesses practices are truly run by data. Nothing latterly moves without it. ML can help a lot in analyzing and finding the interesting connections with the critical set of data.
Machine learning and finance
The machine learning capabilities are extensively used in the better prediction of future trends. Customized apps can analyze all sorts of browser related history of previous transactions and social media activities so that credit ratings can be determined. Such system can also provide a result to consider portfolio optimization and send recommendation directly to the smartphones of users.
The machine learning makes e-commerce simple
ML is providing a number of opportunities to eCommerce businesses in need of increasing the revenue and enhancing their customer experience. Retail giants like eBay and Amazon have already proved how ML can do this. Although, they are big names and, they can make big investments to take advantages of ML capabilities at their workplaces, but smartphone mobility provides easiest ways to implement ML via mobile apps that small companies too can easily afford.
Let’s us come across some examples on how enterprises can intelligently use ML capabilities in their mobile app development projects.
Apps based on the ML technology can provide better product searches in terms of ranking, query-understanding, and the questions related to expansions.
Products recommendation and promotions
With ML, customers get better recommendation for the products they are searching for. The same approach can be applied on the product promotion.
Latest trends forecasting and analyzing
E-commerce companies from the fashion industry require a lot of information to understand the latest market trends. Information related to last year season sales and upcoming trends can them reach more accurately to their customers. Here big data machine learning capabilities aid these businesses to aggregate the trend and sales information from diverse sources and create prediction in real time. The ML can also help fashion businesses to manage better pricing to their products to attract more customers.
Fraud detection and prevention
E-commerce businesses face a number of challenges but with ML capabilities, they can develop a defense system by involving regularly keeping taps on online activities and creating alarms.