Getting Started With Machine Learning
Gartner defines it as follows: “Advanced machine learning algorithms are composed of many technologies (such as deep learning, neural networks and natural language processing), used in unsupervised and supervised learning, that operate guided by lessons from existing information.”
If you haven’t read my last post on artificial intelligence (AI), I recommend you read it here. It will supplement this piece on machine learning core concepts nicely.
In simpler terms, Machine learning is a method that gives a device or computer the capability to “learn” by mimicking human learning. It gathers and learns patterns from massive amounts of data and uses it to make suggestions. It is a subset of AI.
Machine learning is involved in a lot of the technology we use daily. Some examples are Hulu, Netflix, Google, YouTube, Facebook, Instagram, Twitter, and Siri.
The data it needs to collect so it can learn to make predictions are things like your search history, your watch history, your likes, links you click on, and so on. It basically “learns you” and over time and consistency, it’s able to suggest things you will like.
There are 3 main types of Machine Learning. The 3 types of machine learning in the process flow are supervised, unsupervised, and reinforcement learning.
Among the many uses of machine learning in businesses are automation, logistics, fraud detection, increased sales, and improved customer experience.
Automation for digital and financial tasks can be extremely useful for a business in increasing its efficiency, saving time, money, and eliminating human error.
Find out more about our Machine Learning solutions and how they can help your business become more automated by contacting us.