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Machine Learning is a branch of Artificial Intelligence. It contains many algorithms to solve various real-world problems. Building a Machine learning model is not only …
Classification metrics When performing classification predictions, there’s four types of outcomes that could occur. True positives are when you predict an observation belongs to a …
Artificial neural networks (ANNs), usually simply called neural networks (NNs), are computing systems inspired by the biological neural networks that constitute animal brains. An ANN …
A Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a set …
“Data Science” and “Machine Learning” are some of the most searched terms in the technology world. From 1st-year Computer Science students to big Organizations like …
Decision tree learning or induction of decision trees is one of the predictive modelling approaches used in statistics, data mining and machine learning. It uses …
The complexity and quality trade-off Building robust machine learning models requires substantial computational resources to process the features and labels. Coding a complex model requires …
Knowledge acquisition is the process used to define the rules and ontologies required for a knowledge-based system. The phrase was first used in conjunction with …
Knowledge representation and reasoning is the field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system …
In machine learning, support-vector machines (SVMs, also support-vector networks) are supervised learning models with associated learning algorithms that analyze data for classification and regression analysis. …
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