As an important part of Artificial Intelligence, Machine Learning is a transformative technology and methodology that is revolutionizing the modern world. We see Machine Learning being implemented in all industries and sectors across the globe, with companies like Google spearheading its implementation with TensorFlow and other Machine Learning tools.
Machine Learning algorithms improve automatically through the use of data and experience, leveraging Deep Learning capabilities to generate better results each time depending on your goal. Complemented by data science and optimized with the right coding languages, Machine Learning algorithms can help companies build software products, reduce operational expenses, improve efficiency through deep learning, and much more.
In fact, Machine Learning has the power and potential to transform many industries, and everyone looking to build a thriving career should know about the latest Machine Learning trends. In today’s article, we’re taking a look at some key tips and topics on Machine Learning you should know in 2022.
The Growth of Artificial Intelligence and Machine Learning
There is no denying that Machine Learning and Artificial Intelligence are growing in market value and size around the world, and these are becoming increasingly lucrative playing fields. From researchers to companies and the talented people learning Machine Learning and Artificial Intelligence applications, these fields are growing constantly. In fact, the market size is expected to reach 126 billion US dollars by 2025.
According to a report from Founders Legal about the growth of Artificial Intelligence, it’s safe to say that we are seeing an increasing number of use cases for ML and AI in all industries. This is your opportunity to get into the Machine Learning field and build a lucrative career working with neural networks.
There are numerous career paths you could pursue in the AI and ML fields, and taking the first step can seem daunting. Nevertheless, you can find a lot of useful information online and research the best career paths for you, which may include:
- Big data analysis
- Machine Learning engineer
- Human-centered Machine Learning
- Computational linguist
- Machine Learning software developer
- Business intelligence developer
- Natural language processing scientist
As you can see, the clear upward trajectory that the industry is currently on indicates that these positions are going to become more available to the talented people looking to become Machine Learning specialists in the years to come.
Machine Learning in Cybersecurity
As someone who is looking to enter the IT sector and possibly delve into the fields of AI and ML, you probably know that these solutions are being increasingly implemented in cybersecurity. This should come as no surprise, of course, as creating strong passwords and using an out-of-the-box firewall is not exactly the best way for companies to protect their sensitive data.
And so, AI and ML come into play as the essential tools for developing more robust security systems. The applications of Machine Learning algorithms in cybersecurity are endless, and you can use it in service discovery solutions, secure web gateways, firewall testing, preemptive security systems, and more.
Whether you’re designing a solution for different devices and machines in a network to communicate more efficiently, or if you are improving the pen testing capabilities of an existing security system, Machine Learning can help you build more robust solutions over time. In fact, with the advent of unsupervised Machine Learning, you could automate security optimization.
AI and ML in Global Communication
Artificial Intelligence and Machine Learning have become inextricable parts of global telecommunications, but companies are also implementing these systems into their email, direct messaging, and any other communication method. In order for a business to deliver unparalleled customer service, it needs to be available 24/7, and Machine Learning allows you to automate parts of your support department.
Companies can also use AI in email and automate email personalization, scheduling, and many other email marketing tactics in order to generate and convert more leads. When it comes to B2C and B2B communication, the use cases for AI and ML are numerous, and complemented by the aforementioned security systems, companies can ensure safe and secure communication with their customers.
Implementing AI and ML in communication security becomes even more important in a time when online threats become more prevalent. As the cybersecurity threats continue to rise due to an ever-increasing need to use digital communication tools in the workplace and at home, Machine Learning experts will be needed to design systems that will keep people safe.
Using the Right Programming Language
Aspiring developers can choose between some of the top programming languages in 2022, and the more of them you master, the higher the chances that you will quickly build a thriving career. When it comes to Artificial Intelligence and Machine Learning systems, however, you may not need to master several, as you may want to specialize in a single language preferred by your employer or your clients.
Typically, this will be a comprehensive, general-purpose language such as Python, or other multi-paradigm languages used for coding apps and software, and security systems. For example, Machine Learning is used in email security, and it can be implemented in DMARC lookup tools to provide better results, as well as protecting senders and recipients from spam, malicious links and more.
This is just one of the ways you can program Machine Learning algorithms into a specific system such as email, but the use cases and applications are far-reaching.
Machine Learning Experts are in Greater Demand
It should go without saying that all of this market value growth and the sheer number of possible AI and ML applications are driving the need for more talented people in this industry. Given the fact that average software developer salaries are on the rise around the world and that ML and AI are becoming integral parts of software development nowadays, we can expect to see a higher demand for ML and AI experts in 2022 and beyond.
In fact, now is the time to get into the industry if you are an aspiring developer or machine learning engineer. In 2022 and the years to come, the average Machine Learning Engineer salary is expected to rise above the current average of €53,257 in Europe.
These predictions show that job postings continue to pop up at every corner, and you would expect that the average earnings would start to go down. However, the patterns that are keeping the average salaries high are simply talent restrictions. Currently, the industry is advancing at a rapid pace, and the need for talented people continues to rise, while the availability of talent is still very much low in the fields of ML and AI.
The Future of Machine Learning
Beyond 2022, career outlooks in AI and ML are very positive, as the industry will continue to gain in market value, expansion, and capital investments. Without a doubt, the future of Machine Learning is bright, especially for those who decide to start building their careers in this field in 2022 while the demand is extremely high and the talent pool is scarce.
From customer service to IoT systems, cybersecurity, and all the way to Machine Learning as a service, there are many niches in the industry you can become a part of in 2022 and beyond. Depending on your goal and aspirations, you can make the decision to specialize in natural language processing, ML innovation, or any of the possible career paths we have covered above.
The Rise of No-Code Machine Learning
Just like nowadays you can develop an application without any code, we are witnessing a rise in no-code or low-code Machine Learning systems. These systems are innovative solutions developed by specialized programmers and Machine Learning experts to help companies implement Machine Learning into their processes without having to possess a lot of coding knowledge. This also helps with reducing the number of input features and allows ML experts to leverage dimensionality reduction to improve performance.
No-code Machine Learning can be implemented quickly and without the need for debugging, and the process saves time and money. If you are a Machine Learning expert, you can help develop drag-and-drop systems that clients and customers can use to build their own solutions and implement ML and AI into their processes.
This will allow you to innovate software solutions of your own that facilitate unsupervised or semi-supervised learning, for example, which leads us to the next and final point.
Automated Unsupervised Machine Learning
Data science is a vast field, and big data analysis requires the use of AI and ML systems to cut financial waste and ensure efficiency. As automation continues to improve across sectors and industries, ML and AI experts are needed to help automate data collection, reporting, and big data analysis to help businesses thrive in a competitive environment.
Traditionally, this would require a data analyst to feed the information into the ML algorithm in order for the machine to generate new conclusions. With unsupervised Machine Learning being one of the three ML paradigms alongside supervised and reinforcement learning, however, machines can use unlabeled data to study data structures efficiently and draw their own conclusions.
This approach allows the machine to automate many processes and speed up the learning operations. This is possible now that machines are connected to the Internet and have automated access to vast data stores.
As an ML expert, you can work on unsupervised Machine Learning systems that will take the business sector to new heights of success.
Over to You
Machine Learning is a lucrative playing field and a sound model for business development, and many companies across the globe, as well as governments, are investing in ML experts. If you are looking to get into the industry in 2022 and beyond, be sure to keep these tips and trends in mind in order to future-proof your career and capitalize on the opportunities in this growing field.
About the Author
Nikola is a seasoned brand developer, writer, and storyteller. Over the last decade, he’s worked on various marketing, branding, and copywriting projects – crafting plans and strategies, writing creative online and offline content, and making ideas happen. When he is not working for clients around the world, he is exploring new topics and developing fresh ideas to turn into engaging stories for the online community. Find him on Linkedin!
