Category: Artificial Intelligence Technologies

A support vector machine (SVM) is a classification algorithm that classifies data based on its features. An SVM will classify any new element into one of the two classes as shown in Fig. 2.36. FIGURE 2.36 Classification Process using SVM To make our machine learning model learn, we supply input data to it. The SVM algorithm will…

Neural Network (NN) or Artificial Neural Network (ANN) is a machine learning algorithm that is inspired by the biological neuron system and learns by examples. It consists of a large number of highly interconnected processing elements called neurons to solve problems. The algorithm follows a non-linear path and information is processed in parallel throughout the…

Data science has progressed from simple linear regression models to complex techniques but practitioners still prefer the models that are simple and easy to interpret. In this widely used category of algorithms Naïve Bayes algorithm is one of the prominent names as it is not only simple but so powerful that it outperforms complex algorithms…

Clustering is a set of techniques used to partition data into a number of groups, also called clusters. A cluster can be considered as a group of data objects that are similar to other objects in the same cluster and dis-similar to data objects in other clusters. Clustering helps data scientists to identify two main qualities…

Like decision trees, random forests are also a versatile machine learning technique that can perform both regression and classification. They give better performance than decision trees as it does everything for reducing the number of dimensions (or variables), treating missing values, outlier values and exploring data. Random forests perform better than bagged trees as it de-correlates the…

Do you remember the ‘Guess What’ game that we used to play in our childhood? One of us will think of something, and the others had to guess what it is. For that they can ask questions, answers of which will be either ‘Yes’ or ‘No’ based on these clues, the answer is given. For…

In this section, we will read about some widely used classification algorithms. These algorithms predict the probability that the data that follows will fall into one of the predetermined categories. 2.4.1 K-Nearest Algorithm The k-nearest neighbour algorithm is a supervised learning algorithm in which the output value of data is known but how to get…

Regression analysis is a statistical method tool that allow users to study the relationship between a dependent (target) and one or more independent (predictor) variables as shown in Fig. 2.10. This helps the analyst to understand how the value of the dependent variable changes with respect to independent variables. The values to be predicted are usually…

We can better understand the role of machine learning techniques through a very simple definition given by professor Mitchell − ‘A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with…

Artificial intelligence (AI) works by combining massive data with fast, iterative processing and intelligent algorithms, allowing the software to automatically learn to deduce patterns in data. Building an AI system is a process of reverse-engineering human traits and capabilities in a machine. AI is a broad field of study that includes many theories, methods and…