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Boosting is a sequential process, where each subsequent model attempts to correct the errors of the previous model. The succeeding models are dependent on the previous model.


Ensemble Methods mostly are used in winning machine learning competitions by devising sophisticated algorithms and producing results with high accuracy


The K-Nearest Neighbors (K-NN) method of classification is one of the simplest methods in machine learning, it is essentially.


Artificial Neural Networks are the computational models inspired by the human brain.


Random Forest is a supervised learning algorithm. As mentioned in the name, it creates a forest and makes it somehow random.


Support vector machines are a type of supervised machine algorithm for learning which is used for classification and regression tasks.


K-Means is an introductory algorithm to clustering techniques and it is the simplest of them. K-Means is an easy to implement and handy algorithm.


Principal component analysis (PCA) is a technique used for identification of a smaller number of uncorrelated variables known as principal components from a larger set of data.


A Logistic Regression classifies observations by estimating the probability that an observation is in a particular category.


Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide..


Naive Bayes is a probabilistic classification method based on the Bayes Theorem. In general, the Bayes Theorem gives the relationship between the probabilities of two events and their conditional probability.


Linear Regression is an analytical technique used to model the relationship between several input variables and a continuous outcome variable.