Furthering Your Career Through Machine Learning

Today, we're thrilled to welcome digital marketing and machine learning expert, Jeff Bullas, as our guest contributor.

90% of the world’s data has been created in the last two years.

Think about that for a moment…

The earth is 4.5 billion years old, and yet, a minute fraction of time has produced an overwhelming majority of data.

Mind-blowing.

Data. Data. Data.

It’s become an obsession of organizations both big and small.

How do we understand all of this new data, and use it to further our careers, better serve our customers, or progress a cause?

The answer is machine learning.

What is machine learning?

When you ask Siri what the temperature is outside, your Google Home turns on the kettle, or Facebook automagically tags you in a photo - this is machine learning at work.

Basically, machine learning is the process of computers understanding data and providing advice, based on that data, that turns into action.

“Machines learn from data by adapting to those data, recognizing that data vary from one situation to the next” - Thomas Miller, Ph.D.

Data scientists build machine learning models to understand data, and data engineers put those models into practice.

In day-to-day life, these models materialize in products such as Google Home and web applications like Grammarly. They help businesses predict the behavior of customers and adjust their pricing for optimal demand.

The applications of machine learning are restricted only by the data available and the minds of the engineers creating the models.

Understanding the business problem and where the data comes from

A common misconception about machine learning is that it’s taking over from all human intervention.

Yes, machine learning models and implementation can automate a considerable amount of manual tasks. But for the process to work, we need data scientists to understand where the data is coming from, how to interpret it, and how to make automation possible.

Machine learning is replacing some jobs, but it’s also creating new ones. The reality is, 90% of machine learning modeling and application is not automated. It requires teams working in collaboration; engineers, data scientists, and managers, who all understand the business problem a machine learning model is trying to solve or automate.

With this in mind, it’s crucial for managers to be informed about machine learning and the information systems that make it possible.

Even if you’re not a data scientist or data engineer, you can educate yourself about this technology and future proof your career in the process.

Learn the fundamentals of data preparation, modeling, and analysis. Use practical, real-world examples to explore the basics of next-generation techniques like deep learning, artificial intelligence, and natural language processing.

Take it upon yourself to be a leader in the machine learning and artificial intelligence field.

If you want to up-skill in this area, check out the EmergingEd Machine Learning Foundations and Framework online course.

Implementing machine learning in your industry

Understanding the basic frameworks of machine learning is one thing, but industry implementation is much more complex.

If you want to transform your business into a leader in machine learning that drives industry innovation, you need to identify relevant technologies and design architectures, as well as create project life cycles that aid implementation. You need to be familiar with key data science algorithms, data structures, databases, and information systems. All things that are covered in the EmergindEd Machine Learning and Industry course.

There’s no escaping the fact that machine learning is a complex and multifaceted approach to solving business problems with technology. But if it all feels overwhelming now, how will it feel in a few years when all of your competitors are ahead of the curve?

Now is the time for you to be that leader. To be the innovator in your industry.

Are you ready to innovate?

There’s no doubt that big data is a trending topic of interest in business.

But it’s much more than a passing fad…

With more data being created every single day, businesses need to learn how to find meaning from all of it so we can better solve problems and serve customers.

Machine learning models help us filter this sea of information and automate its meaningful use.

If you’re unfamiliar with the concept of machine learning, or feel as if your skills need to be upgraded, now is the time to invest in your future.

The longer you wait, the more chance you and your business will be left behind.

Jeff Bullas is a digital marketing and machine learning expert and the owner of jeffbullas.com. Forbes calls him a top influencer of chief marketing officers and the world's top social marketing talent, and Entrepreneur lists him among 50 online marketing influencers to watch.