How Machine Learning Can Be Used in Android Apps

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If you are even the slightest bit into tech, you will have caught wind of the waves AI has been making over the past years. It is no longer a futuristic concept that was hailed by sci-fi enthusiasts. Artificial intelligence has finally found a way into the everyday life that we know today. From automated technology to online personalization, smart devices, and a lot more – AI is taking the world by storm. Such progress is justified because it is a genuine breakthrough technology that can take a variety of industries to a whole new level of operation and efficiency.

On the other hand, we have smartphones. The staggering advancement of these pocket marvels in usefulness, and the sheer craze that they elicit from the hardcore tech lovers have no bounds. What started as a device to make calls has now turned into a whole lot more. It has become a status symbol, as well as the personal gate to the digital realm of the World Wide Web. Most of us interact with the internet through our smartphones on a day-to-day basis. After all, it is a means for communication, business, and incredible entertainment – Book of Dead Spielen being a case in point. Due to the meteoric rise of smartphones, the development of apps has turned into a very lucrative industry. It is estimated to hit a worth of 407.31 billion dollars by 2026. Thanks to the creativity and proficiency of developers, we have apps that do pretty much everything. One may think that apps advanced pretty far from when smartphones came around, but the next quantum leap is just around the corner.

We now see machine learning algorithms become implemented into the newest apps. It looks like this is going to open a whole new plateau of efficiency in the mobile tech world. More directly, machine learning can help web developers access new dimensions of possibility due to the immense processing power that AI brings to the table. For users, this means that smartphones are about to become even more intelligent, efficient, secure, and entertaining. Let us give you an overview of how machine learning works and what it can do to benefit phone apps.

Machine Learning Basics

Essentially, machine learning is the use of artificial intelligence in a software solution. By using AI, machine learning applications have the ability to automatically learn from experience. An AI-based solution can improve its abilities and understanding exponentially without having to be continuously programmed or updated. This results in an operational system that is quite human-like in its processing structure. The main benefit is that it becomes self-sustaining due to the ability to judge actions, compare them to a wide array of probabilities, and calculate the best outcome. The more data that an AI-powered application has access to, the more accurate it’s algorithms become. There are three main algorithms that machine learning technology uses.

Supervised learning

This type is based on a functioning process that relies on being fed sample data. It learns from associative target responses and is best at processing numeric values, as well as string labels of various sorts. These can include tags, classes, and so on. By understanding the tendencies of a given system of data, the machine learning capabilities can eventually predict what would fit well into a sequence of information.

Unsupervised learning

This type of machine learning can learn solely from example data, without needing to rely on additional associative answers to build its knowledge upon. It can figure out patterns of data on its own accord, using the knowledge of the initial algorithms it is based upon.

Reinforcement learning

Reinforcement learning is a type of machine learning that uses algorithms to make decisions based on environmental factors. Developers can gear such a type of AI to whatever conditions it should react, and, thus, prepare it for being able to react fast and come up with the best, most accurate decisions in a situation.

The Meaning of Machine Learning in Practical Terms

Financial Assistance

Machine learning can do quite a lot when it comes to finances. The abilities of AI lend themselves perfectly to calculating numbers, recognizing tendencies, and predicting outcomes. In practical terms, this means that an app can study your transaction history, calculate a prediction for your expenditure trends, spending habits, and so on. After that, the app can give you valuable financial advice that is completely personalized. Especially for companies, machine learning can prove to be very valuable when it comes to calculating company budgets, helping with annual expenditure insights, and answers on how to optimize it. The same goes for advice on stock trading – machine learning can access enormous amounts of information and turn it into cohesive, practical tips in an instant. Such a service could cost a company loads of money if done by financial consultants or trading advisers. An AI app, on the other hand, costs only a one-time fee when the software is being acquired.

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Gaming Immersion

We don’t want to give you the idea that AI is bland in any way. The truth is that machine learning can be a great enhancer for entertainment purposes. When it comes to Android mobile games, machine learning can take the entertainment experience to completely new levels of personalization. AI is smart, and it can study a given player’s behavior, patterns choice, inclinations, and so on. By doing this, it can communicate with a player in a particular, individualized way. Additionally, AI can shape the storyline, actions, and environment to suit a player’s likes, therefore creating a completely tailored experience for each player. Although we are already seeing this in some games, it looks like the tendency of future gaming will become increasingly more AI-driven to provide people with more intricate, creative, and spontaneous experiences. Do not fret if you like to game on a PC or laptop, machine learning is a multi-platform technology that can be adapted to function on all types of consoles and computers.

Healthcare Monitoring

Mobile applications that are coupled with wearable devices, such as watches, can provide incredible insight into how one is doing physically. Machine learning can act as a doctor of sorts. By monitoring one’s body functions, AI can calculate biological tendencies, give dietary tips, workout advice, and so on, especially for people who are compromised health-wise, machine learning can provide a helpful hand. In case an app recognizes strange bodily activities, doctors can be contacted instantly. In this way, machine learning could predict and protect people from heart strokes, seizures, and other life-threatening situations.

Transportation Aid

Various transportation apps, such as Uber have to rely on a lot of real-time information. Machine learning can easily help drivers, as well as clients with precise calculations on when a vehicle will arrive, what roads should be taken, and what should be avoided. AI can take into consideration traffic jams, excessive fuel consumption, real-time road blockage updates, and so on. Not only can machine learning report data, but it can predict traffic patterns from studying heaps of data from the past.


AI-based personalization solutions are already being used very actively. Popular sites such as Youtube, Amazon, and many others study the behavior of users. By calculating the tendencies of likes and dislikes, machine learning can recommend products, videos, songs, and other things that are likely to be in line with a user’s preferences. On the one hand, this is very convenient for users, on the other, it is an incredible marketing tool for e-commerce companies that want to market products to the right target groups. In some sense, this makes AI-based personalization a double-edged sword. However, while being bombarded with interest-related ads can be annoying, it can also turn out to be very useful when the ad proves to be of real value. The moral judgment of whether personalization crosses lines or not has a lot to do with the transparency policies of companies. This ends up being a moral quandary, but personalization-oriented machine learning, as such, remains a powerful and potentially helpful tool.

We hope that you gained some insight and inspiration about what AI-based machine learning technology is capable of. It is not an exotic concept by any means. We are already using machine learning more than we might know. Smart assistants such as Siri, Google Assistant, Amazon’s Alexa are just a few examples of how the technology has already made it into the daily lives of a lot of people. In a few years, machine learning may just reach completely new levels of usefulness. We are excited about how advanced, online machine learning solutions will impact the mobile apps of tomorrow. What are your opinions on machine learning and apps? What would you like to see in the future of this technology? Please leave your thoughts in the comment section below. We would love to hear your opinions!

Author’s Bio

Alex Norwood is an experienced traveller and an online entrepreneur. He runs a successful eCommerce business and is always on the lookout for new lucrative ways to make money online, and currently trying to be a part-time ghostwriter at Travelling is Alex’s passion, and he has visited over 20 countries in the last 5 years.