Back ## Machine Learning and its superpowers! ## Machine Learning and its superpowers! The Robots are here – during the last couple of years, Big Data and Machine Learning have changed the entire business landscape and reshaped everything we knew was possible. In this article, we will discuss machine learning and how you can leverage this learning technology in your business.

Machine learning is a self-learning method of data analysis, allowing computers to take action, without being programmed to. This is a powerful tool for your business and a whole new approach to automated decision making.

Learning styles and algorithms, you need to know

Machine learning uses different algorithms that can interact differently with each environment, based on their “learning” style. Let’s see how:

• Supervised learning represents the task of interfering a function from supervised training data. In common words, supervised learning means that each input of data has an already established label or result. Here are some of the algorithms that are using this learning method:
• Decision Trees – Based on yes or no type of answers, the decision tree algorithm structures the analyzed problem or situation so that you can easily make a reasonable decision or arrive at a logical conclusion.
• Naïve Bayes Classification – This algorithm is very common, especially in marking emails as spam or in face recognition software. It’s a simple equation that is based on the Bayes theorem. The equation looks like this: P(A|B) = P(B|A) P(A)  /  P(B), where P(A|B) represents the posterior probability, P(B|A) is the likelihood, P(A) is the class prior probability, and P(B) is the predictor prior probability.
• Ensemble Method – Based on the prediction, the ensemble method builds a set of classifiers and then classifies the data by analyzing their predictions.
• Unsupervised learning represents the situation where the input data has no established labels, so the algorithm needs to show a result, all by itself. Google uses unsupervised learning for analyzing tens of millions of YouTube videos. Here are some algorithms that are using this type of learning
• Clustering Algorithms – Grouping different objects based on a certain pattern
• Independent Component Analysis – Revealing hidden factors and defining a generative model for analyzing multivariate data
• Semi-supervised learning, which is a mix of the above two learning styles, where you have a large amount of input data, and only a part of it is labeled.