Machine Learning 101

Updated: May 21, 2020

Machine learning falls within the field of Artificial Intelligence. It is actually quite fascinating, powerful, and full of potential.



What is Machine Learning?

Essentially, machine learning methods enable systems to learn from the data and experiences they process. For most of the digital age, computers have required human intervention. We typically program the computer to execute commands we code and process data we intentionally enter into the system. Today, computer systems are able to learn automatically without human intervention or the need for human adjustments. They are able to process historical and real-time data to learn and adjust all on their own. They are able to do so by using sophisticated algorithms to identify patterns in the data. The systems then use this new information for decision making.


Just think about all the data that is out there about you, me, financial markets, medical research and so much more. The possibilities are endless.


What can we do with Machine Learning?

There are many areas where machine learning can be leveraged.

In the medical field, it can be used to assist in medical diagnosis and prognosis. It the financial field, it can be used for predictive analytics. In fact, you probably already interact with some degree of machine learning if you use platforms such as Facebook, Amazon, etc.


What programming language is used for Machine Learning?

After looking into this a bit, it seems that most would agree that

Python is the most popular programming language used for machine learning.



Machine Learning Methods?

Although I am sure there is still much development and growth to come from the machine learning, some methods used today are:


  • Supervised machine learning algorithms

  • unsupervised machine learning algorithms

  • semi-supervised machine learning algorithms

  • Reinforcement machine learning algorithms


I'd be interested to hear your thoughts on machine learning in the comment section below!

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