Machine learning has stolen many of the technology and electronic headlines in the last few weeks.  Thus we feel the topic Machine Learning should take precedence over our ongoing series on types of business-boosting videos.

However, our series on types of videos that enhance your bottom line is practical and down to earth.  We feel you demand that information.

Meanwhile, we know you also want the latest technological trends in electronics, business, and industry.  So we experienced some consternation in deciding which topic to share in this blog.

Machine Learning connects humans to computers in a meaningful way.

As machine learning matures, we will have new and better ways to connect to data.

The Tall Order of the Bullhorn Blog

Almost every Bullhorn Media blog involves a writer’s decision like this one.

In our media industry, electronic news and technological innovation are in constant flux.

So today we have decided to bring you a little introductory theory behind all the hype about Machine Learning.  But do not worry, one day soon we will return to our practical lessons in choosing a video product to boost your business.

Thus we interrupt our regularly scheduled programming to catch you up on basic news in Machine Learning.  If your business is small, you probably won’t utilize it tomorrow.  But you should have known about it yesterday.  And you will probably be using it in the future.

Machine Learning, AI and a Definition

Why?  Because “machine learning”  is the phrase you will be hearing in the hallways of industry, cocktail parties, and in important little coffee-fueled conversations for a long time to come.

Machine learning is a method of data analysis.  Experts tell us that machine learning automates analytical model building.  It is a branch of artificial intelligence. 

You can’t talk about Machine Learning without mentioning AI. By review, remember “AI makes it possible for machines to learn from experience…”

Let’s Look at a Quick Summary of the Powers of AI:  A Quick Review

  • Artificial Intelligence can adjust to new inputs.
  • Likewise, it performs human-like tasks.

A Quick Side-Note About Natural Language Processing

The examples of AI you know would include chess-playing computers and self-driving cars.  They rely on deep learning and Natural Language Processing.

Beyond code, NLP “is a branch of artificial intelligence that helps computers understand, interpret and manipulate human language.

Wow, they speak English– and any other dialect of any language, which is a lot faster than speaking only in code!

Machine Learning allows us to better communicate with machines.

Machine Learning makes it possible to bypass the coding, just talk to the machine.

  • Natural Language Processing draws on computer science and computational linguistics.  Its goal is to clarify communication “between human communication and computer understanding.”  For more about AI and NLP, visit the experts at this helpful online source.
  • At a basic level, you are using these technologies when you say, “Seri, call Bob Johnson!”  Or “Alexa, turn on the lights, medium-low.”

Now, Off our Detour and Back to Our Machine Learning Discussion:

To put it Briefly, using these NLM technologies, and machine learning, computers with AI, can be trained to accomplish specific tasks. They learn by processing large amounts of data.  Then, they recognize the patterns in the data.

Machines (Systems) And Learning from Data

Machine Learning is based on the main idea that systems can learn from data.

  1. Thus, using machine learning, a computer can identify patterns.
  2. Then here is where it becomes amazing: With machine learning, the computer makes decisions based on those patterns.
  3. Key to the above two steps is that human intervention is minimal.

Simplifying  The Machine Learning Concept

To put it simply, machine learning “is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.” That is what we are often tempted to call magic.

Why is Everybody Buzzing about Machine Learning?

Obviously, any concept that has so many theoretical layers is more easily understood once we can understand what on earth we can DO with it.  So, let’s look at a few examples:

  1. Shopping With Machine Learning: You have probably encountered shopping assistance from Amazon or Netflix.  Those helpful online recommendations come from machine learning applied to everyday tasks.  Building Business with Machine Learning:
  2. Building Business With Machine Learning:  If you own a business and you are constantly aware of what all your customers are tweeting about you, then Machine Learning is helping you with your bottom line.  You might not need to know the magic behind this is termed “machine learning combined with linguistic rule creation.”   You just need to know it’s working.                 It’s keeping you aware of all those happy tweets.

More Serious Applications for Machine Learning

  1. Machine Learning In the War on Fraud: Did you get the latest fraud alert? Can you protect your family from the newest online scams in taxes and/or higher education?  If your answer is yes, then you have probably discovered one of the most critical “obvious, uses of Machine Learning in our world today.”
  2. Cyber-net Protection: Find out how the technology is protecting you and your bank at this informative online resource.

Furthermore, You’ll Feel the Impact from these Entities Who Adapted Machine Learning before it Was Hype:   

  1. The Oil and Gas industry: Machine Learning is making oil distribution more efficient and cost-effective.  Likewise, it assists with
    Machine Learning brings timely data to a doctor's life-saving diagnosis.

    Bringing Your  Doctor life-saving Data at Light Speed.

    finding fuels in the first place, which is a great help.

  2. Financial Institutions:  Machine learning is not only busy detecting fraud but also minimizing identity theft.
  3. Last But Not Least:  The Government–“Government agencies such as public safety and utilities have a particular need for machine learning since they have multiple sources of data that can be mined for insights.” We can easily see that “Analyzing sensor data, for example, identifies ways to increase efficiency and save money.”
  4. Health-Care:  With wearable health sensors, machine learning is helping collect life-saving data at home and in the hospital.

Getting Started on Vocabulary for Innovative Technology

Just in case you get involved in an artificial intelligence conversation, we thought you might like to have a few insights about the jargon.  Yes, this is simply a few basic vocabulary words, but just listen for these terms:

  • In reference to machine learning, a target is termed a label.
  • In contrast, you will note that in statistics, a target is called a dependent variable.
  • On the one hand, a variable in statistics is referred to as a feature when used in machine learning.
  • On the other hand, a transformation in statistics is called feature creation in the technology of machine learning.  Of course, if you do not know too terribly much about statistics or machine learning, look on the bright side.  You won’t become confused by the overlapping vocabulary.

A Video Assignment for You:  We Promise It’s Cool!

On the one hand, artificial intelligence (AI) is the broad science of mimicking human abilities.  On the other hand, Machine Learning is a specific subset of AI that trains a machine how to learn. We suggest you watch a short video at this online resource.  In two minutes, you will be ready to talk about this timely topic.

Plus, you’ll see how SAS corporation took this complex theory and created a brief instructional video in basic easily understood language.   It’s a good example of how all today’s technologies including video weave together to create life in the 21st century.  And, it is an entertaining little video.  Likewise, you will see how machine learning can help any business in any niche.  And you’ll know this new technology isn’t really magic. It just seems like it.