If you take a look at the current set of events, you will see that machine learning is a hot topic in the world of technology. Software developers from all over the globe use this technology to make their apps more efficient. You will see that some of the biggest companies out there have decided to use it for their software to improve it.
These days, it is easier to use machine learning than ever before. The reason why this is the case is that we can use the technology known as Core ML, which is an iOS exclusive. If you are interested in the Android option, you should look toward the ML kit. Depending on your company’s needs and preferences you will choose one of these.
In reality, we can see that machine learning is considered a part of AI, which serves as an umbrella term for a wide array of different technologies. Today, we would like to provide you with a couple of ways Singapore startups can use Apple’s Core ML to develop iOS applications with smart AI features. Without further ado, let’s take a look at some of the relevant points.
The first thing we would like to talk about is the benefit of using data mining in app development. They can help with developing non-obvious patterns and connections with a set of data. Data mining has three main stages, data storage, maintenance, and the analysis of the data gathered during the process.
Machine learning provides all the necessary tools to conduct this sort of operation. We can all agree that it is impossible for human beings to conduct such operations and find all the variations needed to predict customer behaviour patterns. Better yet, data mining can be connected to your social media accounts, which helps with gathering all the data.
Gathering all the data is a structured procedure, which means that it consists of a couple of important segments. It will be categorised through gender, age, behaviour, preferences, etc. Having an insight into all of these is what makes data mining an exceptional advantage for app building in this day and age.
Easier to Define App’s Structure
A couple of years ago, the only way for app developers to define the structure of their apps was to reach out to the external server. The same process was needed to enable the AI features. These days, we can see that machine learning offers a completely new angle through running data analysis and fetching the features from a server.
At the same time, we can see that GPUs and CPUs, which are quite faster today, and machine learning chips we can find in mobile phones of new generations, we can reach out for these much easier. Defining the app’s structure is an absolute must since it will help the development process.
Making Ads More Relevant
Every company out there, no matter the size, strives towards making its ads as relevant as possible. You will certainly agree that beating the competition is not easy these days, and you will need to invest as much effort as possible before you can make it possible for the ads to reach out to more people.
The days when apps displayed on your mobile phones didn’t have anything to do with your interests are long gone. Startups can use machine learning to make relevant ads about their products or services. If potential customers are targeted right, then there is no doubt that the number of customers will increase significantly.
Machine Learning has done a lot in the field of making ads way more personalised. Whenever a company is about to release a new product or offer some promotions, this is the right way to go. By reaching out to more potential customers, the chances of increasing the number of those who will become loyal to the brand tend to rise significantly.
The next thing we would like to point out is the importance of Apple’s Core ML when it comes to searching. Machine learning can do a lot with gathering all the information about an individual’s search query, clicks, and screen scrolls. All of these make for exceptional help in situations when the app tries to predict the behaviour of a customer.
Thankfully, it is possible to use the information in front of you to predict these preferences. By doing so, you will get a polished look at how people think, and what can attract them to use your app in the future. Naturally, studying this information is quite challenging and that’s the moment when machine learning comes to the stage.
Machine Learning for E-commerce Apps
Last but not least, we would like to talk about the use of machine learning for e-commerce apps. Without any doubt, this will be one of the cornerstones of the future of e-commerce. It is interesting to know that stores like Amazon have already implemented this method and that they use it for suggesting products to their clients.
For a long time, this approach was largely underestimated, but we can see that it has become a prevalent option for many newly-built e-commerce sites. It monitors the products consumers are clicking on and helps with predicting their future decisions, alongside providing them with recommended products.
Among other examples of sites that use this approach, you will find ones such as IBM, Microsoft, or TensorFlow. A good thing about this option is that you can always add some open-source APIs, which will make the system even more efficient in the future. Accessing these is easier than it has ever been and you should make the most of them.
Singapore startups are among the fastest-growing ones in the world since the country has decided to invest significant amounts of money in these. Here, you can take a look at how local startups can use Apple’s Core ML to make their apps smarter and more efficient. We are certain that you will find this article of ours particularly helpful in this regard.