Essentials of Machine Learning Algorithms (with Python and R Codes) – Part 7

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K-Means

It is a type of unsupervised algorithm which solves the clustering problem. Its procedure follows a simple and easy way to classify a given data set through a certain number of clusters (assume k clusters). Data points in…

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Essentials of Machine Learning Algorithms (with Python and R Codes) – Part 8

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Random Forest

Random Forest is a trademark term for an ensemble of decision trees. In Random Forest, we’ve collection of decision trees (so known as “Forest”). To classify a new object based on attributes, each tree gives a classifi…

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Essentials of Machine Learning Algorithms (with Python and R Codes) – Part 6

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KNN (K- Nearest Neighbors)

It can be used for both classification and regression problems. However, it is more widely used in classification problems in the industry. K nearest neighbors is a simple algorithm that stores all availab…

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Essentials of Machine Learning Algorithms (with Python and R Codes) – Part 4

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Decision Tree

This is one of my favorite algorithm and I use it quite frequently. It is a type of supervised learning algorithm that is mostly used for classification problems. Surprisingly, it works for both categorical and continu…

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Essentials of Machine Learning Algorithms (with Python and R Codes) – Part 5

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Naive Bayes

It is a classification technique based on Bayes’ theorem with an assumption of independence between predictors. In simple terms, a Naive Bayes classifier assumes that the presence of a particular feature in a class is un…

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