What is Machine Learning?

October 27, 2022


phone, fintech notebook, and coffee cup on table, with a hand over the notebook with a pen.

Machine learning is exactly what it sounds like: teaching a machine to learn! This type of technology is a branch of Artificial Intelligence and computer science. It is a very vast (and fun) type of technology that is becoming a growing area of IT, meaning a good place to look for a career. 

How does a machine learn?

UC Berkeley says machines “learn” in 3 parts: 


  • A decision process– A series of calculations or other steps that considers the data and “guesses” what kind of pattern your algorithm is looking to find.
  • An error function– A method of measuring how good the guess was by comparing it to known examples (when they are available). If the decision was wrong, the program calculates “how wrong” it was. 
  • An updating or optimization process– A method in which the algorithm looks at the miss and then updates how the decision process comes to the final decision, so next time the miss won’t be as great.


You can find an interactive and visual introduction to machine learning here: http://www.r2d3.us/visual-intro-to-machine-learning-part-1/


Types of Machine Learning

Machine learning is a very broad field, but can be broken up into 3 main categories:


    • Supervised learningthis is characterized by its use of labeled datasets. As data is input into this type of model, its weighed and categorized. You see an example of supervised learning when your email characterizes a message as important or spam. 
  • Unsupervised learningthis is characterized by its lack of labels for the datasets. The machine decides what data it needs to categorize by recognizing patterns in the inputs. 
  • Reinforcement learningthis type of learning is similar to unsupervised learning in that it doesn’t have labeled datasets. As it learns the model is given an input related to its decisions, so the model gets better the more it runs. Think of a robot learning to walk, it can try different strategies and learn what works best to bring it the furthest distance based on what happens in its environment. 

Real-world applications

Machine learning is increasingly evident in our day-to-day lives. IBM says we can find machine learning in all kinds of scenarios, including customer service, fraud detection, and speech recognition. It is making our lives easier by automating routine things that would otherwise be laborious and time-consuming. 

Jobs in machine learning

There is a lot of opportunity in machine learning. Some job titles to look out for include Software Engineer, Data Scientist, Cyber Security Analyst, and Machine Learning Engineer. ZipRecruiter says the national average for a machine learning engineer is $117,363 a year. 


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