ML - Machine Learning

ML or machine learning is a subfield within AI or artificial intelligence that deals with the construction and study of algorithms that can learn and make predictions on and about data. Machine learning refers to the method of teaching computers to learn from data, without being explicitly programmed. 

Machine learning algorithms build a mathematical model based on sample data, known as "training data", this training data support the computers to learn and teach themselves. Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or impractical for humans to write rules to perform the necessary tasks.

There are three main types of machine learning:

Supervised learning: The computer is presented with example inputs and their desired outputs, given by a "teacher". The computer is then forced to learn the general rule that maps inputs to outputs.

Unsupervised learning: No labels are given to the training data, leaving the algorithm to try to find structure in its input.

Reinforcement learning: A computer program interacts with a dynamic environment in which it must perform a certain goal. The program is provided feedback in terms of rewards and punishments as it navigates its problem space.

All three learning types create machine learning. Machine learning is a helpful tool that can decrease the number of human hours spent on a task. This supports the overall efficiency of your business.

How does Machine Learning work?  

Machine Learning works by using algorithms to identify patterns in data, and then using those patterns to make predictions or decisions. The algorithms can be trained with labeled data, which means they are given input data and the expected output. The algorithm then learns how to map the input data to the desired output.  

What are some applications of Machine Learning?  

Some applications of Machine Learning include predictive analytics, computer vision, natural language processing, robotics, and more. It can be used for tasks such as image recognition, speech recognition, recommendation systems, fraud detection, and many others.

Fun Fact:

"According to a survey by Gartner, more than 85% of organizations are investing or planning to invest in Machine Learning (ML) for their business operations by 2020." (Gartner, 2019).

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ML - Machine Learning