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What is Machine Learning?

Computers⁠—while versatile and able to perform a myriad of tasks⁠—still need a human to program them. If the code is faulty, it needs a human to fix it, so the computer produces the desired outcome. But what if the computer does this on its own?

Machine Learning is a way for computers to learn and improve their performance on a given task. It mimics how the human brain functions. The computer is made to do the tasks hundreds of times each time. Just like real brains, a machine uses interconnected neurons to do the learning.

The human’s role in processing is to provide quality data and precise instruction—kind of like a mentor or a teacher. Machine learning professionals design the AI and feed it good and clear data to ensure that the AI learns correctly.

This new paradigm has many potential applications, from scientific research to business and economics. Machine Learning also touches on several disciplines like Computer Science, Artificial Intelligence, Mathematics, and Linguistics. This makes it one of the most promising fields today, attracting hundreds of talents annually.

What skills do you need as a Machine Learning professional?

Like many highly technical fields, Machine Learning requires certain specialized skills. As it puts major emphasis on research and development, professionals looking to make a career in the industry must be proficient in several technical know-how. Here are some of the most important skills to hone:

Computer Science Fundamentals 

Computers are the heart of the Machine Learning revolution. That is why a good grasp of Computer Science fundamentals is a must for aspiring machine learning professionals. You need to be well versed in data structures, algorithm concepts, and decent programming skills. Database management is also a good skill to have.

Software Development 

A common misconception is that programming is software development. This is not entirely the case. There is a lot more that goes into designing and developing software. A software developer in the machine learning space needs to expertly design software that’s up to spec. They are also expected to be able to optimize this software to make them more efficient.

Data Science 

A popular adage in computing goes, “Garbage in, garbage out”. This pertains to how bad input data results in bad output. This is why machine learning professionals need to be skilled in processing, vetting, and analyzing data. It is important that the data that is fed to the AI is free from error and are of high quality. This makes sure that the AI gives the desired output.

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This soft skill is indispensable in the world of Machine Learning. In the field, professionals are expected to be able to collaborate with other professionals effectively. Documentation and paperwork also play a major role. Being able to communicate effectively is a huge advantage for aspiring professionals who wish to make a career in Machine Learning.

Machine Learning careers

Given the fact that Machine Learning is one of the most popular fields in today’s world, it is also full of opportunities. Its application to several other fields allows professionals from different backgrounds to enter. Here are a few of them:

Software Developer

Right off the bat are the actual people who write and design code. Software Developers are in demand in a variety of fields and industries. They are also some of the highest-paying careers today. Developing software specializing in Machine Learning is more lucrative given the highly technical nature of the job. Their .

Machine Learning Researcher 

As a relatively new industry, companies and institutions invest much into research and development. And innovations in the field are all thanks to researchers. They perform tasks such as documentation, testing, and development, among others. The .

Data Scientist 

While having a good grasp of data science is a great skill for all ML professionals, Data Scientists specialize in it. They are professionals who are highly trained in data science and the many techniques in the craft. They excel in data analysis and recommending measures based on these analyses. The .

Machine Learning Engineer 

Though they perform a myriad of tasks, a Machine Learning Engineer’s primary role is the development of Machine Learning systems. They are the primary actors in designing AI, gathering and optimizing data, and training the AI. They are also responsible for experimentation and testing. In the US alone, a Machine Learning Engineer .

Machine learning for business

Outside research, one of the fastest-growing applications of Machine Learning is the business sector. Companies are seeing the potential of using AI to crunch and process large amounts of data at blazing fast speeds. This lets them take actions based on these data at record speed. Here are some of the careers that would do great in the business sector:

Business Intelligence Developer

In a nutshell, Business Intelligence Developers translate data into easily understandable insights for businesses. They are focused on gleaning business insights that would help a company grow. They use a variety of software and other Business Intelligence techniques and best practices to make this happen. They collect and interpret data and make detailed reports based on them. A BI Developer’s .

Data Analyst

Though a Data Analyst and a BI Developer perform generally similar tasks, they are distinct. Data Analysts are tasked to solve several problems that are not necessarily directly tied to business growth. They work with Machine Learning Developers to make sure that the data used for training the AI is sound. They have an .

Business Automation Specialist 

These automation experts are focused on improving and streamlining business processes. They use a variety of tools including Machine Learning to optimize processes. They provide solutions that

Machine learning job growth

Career advancement in the Machine Learning sphere is also rewarding. There are several good career paths to choose from. This is perfect for those looking for highly rewarding opportunities that offer personal and professional growth. Here are a few of them:

Machine Learning Team Lead 

As a hugely collaborative field, there will be many heads working on any given project. A Machine Learning Team Lead is responsible to manage these teams. They are tasked to address the needs of each team member while optimizing and maximizing output. They are also responsible for helping the team grow by helping individuals advance in their careers. Their average .

Machine Learning Engineers 

Given enough experience and adequate qualifications, one may advance into the Machine Learning Engineer role. They are responsible for the in-depth development of algorithms and systems that require advanced skills. They may also work as project leaders that handle teams of developers and researchers. They earn an .

Senior Software Developers for Machine Learning 

This is a step up for software developers looking to advance their careers. While they may need to perform most of the tasks as software developers, they are tasked with other admin roles. They are expected to be able to manage smaller teams and serve as project managers.

How to get a job in machine learning

While far from easy, breaking into the Machine Learning scene is doable even at entry-level. But, like many highly technical fields of endeavor, there are specific things you must have. Fortunately, there are many opportunities available these days to accomplish these.

Network network network 

Never underestimate the power of having an extensive personal and professional network. Meeting and knowing people in the industry is the best way to find information and opportunities in the career you want to pursue. Always make it a habit to meet up with other talents and maintain good professional relations.

Another way to gain a sizable network is through social media. Places like Facebook and LinkedIn are great places to meet new and interesting people in the industry. Try joining Facebook groups and join in on the discussion. Reach out to individuals on LinkedIn and spark conversations whenever you can. Regularly connect with others and interact with them.

Keep up to date with industry news 

“Knowing is half the battle” as the old saying goes. In this day and age, information is the name of the game, especially in Machine Learning. Online forums like Facebook and Reddit are great sources of up-to-date news. Online discussion boards and forums are a goldmine of information.

Keynotes, lectures, and seminars are also great sources of what’s new in the industry. Make it a habit to attend these events as much as possible. News are great ways to learn about recent breakthroughs as well as opportunities.

Join relevant events 

While events are great ways to connect with others as well as get the latest news, they are fulfilling in and of themselves. They are great ways for exposure and experience, especially for those looking to get into the industry. They teach you how to interact with fellow professionals as well as give a venue for you to geek out and talk about Machine Learning and other interests.

Expos and conventions are also great things to go to. This is the time when various companies come to showcase their projects and the latest innovations. They are also great for beginner and experienced professionals alike to showcase their skills and meet companies willing to invest in them.

Take the necessary degrees 

Having relevant degrees is still the best way to get a shot in the Machine Learning industry. You can do this through universities and colleges. These days, there are more options available. Online institutes, like ��������, let you learn the necessary courses to be competitive in the field as conveniently as possible.

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