By Anastasia Stefanuk
Machine learning is one of the most critical skills developers must have in the current IT industry. As this data analysis and automation technology continue to grow in popularity, many businesses are looking to find Android developers who are skilled in building applications with ML. The branch of AI started off differently than what it has grown into today, and we can only expect to see the technology continue to transform in the years to come.
What Is Machine Learning?
Years ago, machine learning emerged from a theory that computers can learn from data. Rather than being programmed to perform specific tasks, the idea was that computers could autonomously acclimate to new data and gather results based on previously used calculations. Several machine learning algorithms have been around for years, but the ability to analyze big data and deliver complex mathematical calculations in today’s machine learning (think self-driving cars and online recommendations) is a recent development.
If you aren’t in the field of IT, it might be difficult to understand what we mean when we talk about data, algorithms, and autonomous calculations. So simply stated, machine learning is used in a variety of places in your everyday life without you even realizing. Some examples of ML you might use every day are:
- Virtual personal assistants such as Siri and Alexa
- Commuting predictions such as traffic and delays used on GPS or apps like Waze
- Video surveillance systems that alert humans to movement
- Product recommendations based on your previous shopping interests
- Online fraud detection that automatically compares your transactions to alert suspicious activity
- Social media services like Facebook’s “People You May Know” and facial recognition to tag photos
As you can see, machine learning is an essential component for many of the resources you use today. That’s why developers have become proactive in studying the ML skills and putting what they learn in the machine learning course to use in the IT field.
ML Usage in Android Software Development
Android app developers have become the most proficient users of machine learning in the past few years. That’s because common mobile apps used by Android and iOS users are constantly involving to offer more in terms of AI. From finance and healthcare industries to transportation and food delivery businesses, mobile apps need to offer users a better experience if businesses want to compete with the leaders of their industry. That’s where machine learning comes into play.
Some of the most common machine learning apps created by an Android developer include:
- Oval Money
Mobile Apps That Implement ML for a Better User Experience
Businesses everywhere have discovered the benefit of using machine learning to their advantage. Companies across a variety of industries are integrating popular technology into their mobile apps. As this AI becomes one of the key technology trends amongst developers, you can see its use in things like:
- eCommerce apps- Machine learning allows eCommerce businesses to provide customers with a better user experience through product recommendations. Based on user preference and past search trends, these apps can recommend similar or complementary products for users.
- Picture editing apps- Today’s average mobile user has at least one picture editing app on their mobile device. With the insane popularity of social media, picture editing apps are extremely popular right now. ML allows these apps to offer sizeable layout choices and a variety of filters to transform pictures instantly.
- Weather forecasting apps- The use of machine learning in weather forecasting allows apps to identify your current location and gather weather forecasts relevant to where you are.
- Food delivery apps- Restaurant apps are very popular right now and with the introduction of Uber Eats and GrubHub, customers are downloading these apps in record numbers. According to one study, GrubHub processes around 220k orders a day and serves a whopping 15.1 million active diners. These apps allow you to place orders, ask questions, and provide you with real-time delivery tracking.
- Healthcare apps- Thanks to machine learning, healthcare apps can analyze your symptoms, provide possible conditions, and offer treatment and prevention suggestions. Wellness apps can help you track your weight, fitness schedule, and even calories burned and step taken.
5 Facts About Machine Learning for Android Developers
If you are considering diving into the world of machine learning as an Android developer, you’ve made a wise choice. Here are some important facts every Android developer should know before they get started.
1. ML Is Limitless When It Comes to Application
As mentioned above, there are already so many fields that have integrated ML into their everyday processes. From education to finance and computer science, there are no fields where machine learning doesn’t apply. In fact, in many different industries, machine learning is desperately needed for further advancement. For example, the healthcare industry continues to use research to create a foundation for medical advances. Machine learning can impact medical scan analysis as it compares big data across the world. Where other technologies eventually fall off the grid, you don’t have to worry about the future of ML.
2. ML Development is Heavily Focused on Mathematics
When it comes to ML, there is, unfortunately, no way around the math behind the technology. Learning how to use technology in your development will require you to spend a lot of time and work committed to the mathematical process. This is one of the most frustrating parts of fully learning the technology for developers. The good news is that while it is important to understand all the math behind the technology, many developers have found ways to use various tools to apply the technology through the learning process.
3. Cross-Platform Products Can Give You a Look into Android Programming
It’s necessary to complete all the courses and tutorials related to the mathematical component of the technology at some point. But, some developers have found that putting the technology into practice throughout the learning process has helped them to stay motivated. Some popular Android tools include:
- Google Cloud AutoML
- Firebase ML Kit
- Fritz Mobile SDK
- Using these apps during the learning process allows you to further understand the technology and get a glimpse into its possibilities.
4. Tensorflow Is Hidden Gem
Whether you are a beginner or an old pro when it comes to app development using ML, Tensorflow will be your right-hand person. The end-to-end open source platform offers a variety of tools for its users. This includes community resources, comprehensive libraries, and Android forums. It will be an essential tool for creating, training and running your machine learning models.
5. Machine Learning Will Open the Door to New Career Possibilities
Now that you understand the common problems ML developers face and resources to help, we’ll leave you with a look into the world of possibilities when it comes to the technology. Machine learning jobs are on the rise as more and more businesses look for app development with machine learning. The complicated mathematical component of this technology does prevent developers from finding the motivation to learn.
If you can plow past that lack of motivation, machine learning will offer better career opportunities. The lack of machine learning skills in the industry means higher demand, so you’ll never be lacking work. Finally, developers with machine learning skills make a good salary with average yearly results commonly over $100K a year.
Don’t underestimate the power of this rapidly rising popular technology. There is no telling where the future will go when it comes to machine learning. There is no doubt wherever it goes, it’ll be far.
Anastasia Stefanuk is a passionate writer and a marketing manager at Mobilunity. The company provides professional staffing services, so she is always aware of technology news and wants to share her experience to help tech startups and companies to be up-to-date.
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