Machine learning (ML) is important because it gives enterprises a view of trends in customer behavior and business operational patterns, as well as supports the development of new products.
Many of today’s leading companies, such as Facebook, Google and Uber, make machine learning a central part of their operations.
Machine learning is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Algorithms are an important aspect of machine learning because algorithms use historical data as input to predict new output values.
The type of algorithm data scientists choose to use depends on what type of data they want to predict. One of the most common types of algorithm is called a linear regression.
In this algorithm a relationship is established between independent and dependent variables by fitting them to a line. This line is known as the regression line and represented by a linear equation Y= a *X + b.
Another common kind of machine learning algorithm is the decision tree algorithm. This is a supervised learning algorithm that is used for classifying problems. It works well classifying for both categorical and continuous dependent variables. In this algorithm, the population is split into two or more homogeneous sets based on the most significant attributes/ independent variables.
There’s also the SVM (Support Vector Machine) algorithm, a method of classification algorithm in which you plot raw data as points in an n-dimensional space (where n is the number of features you have).
The value of each feature is then tied to a particular coordinate, making it easy to classify the data. Lines called classifiers can be used to split the data and plot them on a graph.
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Participants learn differences and similarities between Machine Learning, Artificial Intelligence, Deep Learning, Data Mining and Data Warehouse. Artificial Intelligence uses models built by Machine Learning to create intelligent behavior applied to businesses, marketing and sales, operations, autonomous cars, games and industrial automation by prediction based on rules and using programming languages and algorithms.
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