Supervised Machine Learning – Insider Scoop for labeled data

Supervised Machine Learning is a type of system in which both input and desired output data are provided.


This is our first post in this sub series “Machine Learning Type” under master series “Machine Learning Explained“. We will only talk about supervised machine learning in details here.

Machine learning algorithms “learns” from the observations. When exposed to more observations, the algorithm improves its predictive performance.

Machine Learning for Businesses

Supervised Learning is becoming a good friend for marketing business in particular. For example how much money will we make by spending more dollars on digital advertising? Or even making small predictions for stock markets i.e. What’s going to happen to the stock market tomorrow?

Machine learning techniques are accelerating almost on a daily basis with intentions to bring good values to the businesses of today. It is revolutionising the way we do our business and what should be done to improve upon. On high level we got three main type of Machine Learning types i.e. Supervised, Unsupervised and Reinforcement learning. Since this post is limited to supervised learning and what it is doing in business; so I will stick to it only for now.

Supervised Machine Learning -SML

Lets understand a bit about SML and find answers around what it does, how it does, and what it can do for our real life business.  Supervised learning through historic data set is able to hunt for correct answers, and the task of the algorithm is to find them in the new data.

How its powering our businesses to make sure we survive and get best out of what we do. Supervised Machine Learning is

  • Is a task of deducing function from labeled training data.
  • Making predictions based on evidence in the presence of uncertainty
  • Identifying patterns in given data with adaptive algorithms

Points to Note:

All credits if any remains on the original contributor only. We have covered supervised machine learning where we make predictions from labeled historical data. In the next upcoming post will talk about unsupervised machine learning.

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