Why Machine Learning?

Neural Network (via ExtremeTech)

Machine learning algorithms continue to become an increasingly vital component of software. Today, numerous companies utilize machine learning algorithms to create predictions. In case you were curious about where you may see these prediction algorithms in action; take a look at those personalized recommendations visible on sites such as Amazon, Target, Facebook, or even on Google’s search page. But why learn machine learning? The answer is simple. Machine learning is a concept, if utilized properly, that can increase efficiency for any company. From startups to large corporations, companies are continuously looking for teams or employees that can implement machine learning at their core in order to increase efficiency. Adding topics of machine learning to a resumé and to a quiver of skills will increase value to employers drastically. Even for non-engineers, understanding what machine learning can do for their businesses and how to utilize it will provide a high return. As for engineers, machine learning paves the way for the innovative technology continuously being introduced. The concept allows for cars to drive and think for themselves, smart home technology, prediction software, and countless other innovations.

“I can’t quite tell exactly but advances in AI and machine learning, we are making a big bet on that. Advances in machine learning will bring a difference in many many fields.” — Sundar Pichai (CEO, Google)

The theories behind machine learning concepts have been around for years. Topics include fuzzy logic, decision trees, artificial neural networks, evolutionary algorithms, supervised or unsupervised learning, and much more. In order to understand any topic or concept, the first step is to find resources. Linked below is a post that explains how to get started with machine learning written by Daniel Hanson.

How to Get Started in Machine LearningA quick guide listing a few ways to get started with ML

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