Machine Learning
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Machine Learning
Part 1 of 6
Linear Regression
Introduction Linear Regression is a supervised machine learning algorithm which finds a best fit line between a dependent variable and one or more independent variables. This means that linear regression finds a linear relationship between dependent ...
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Support Vector Machines(SVMs)
Introduction The objective of the support vector machine algorithm is to find a hyperplane in an N-dimensional space (N — the number of features) that distinctly classifies the data points. Hyperplanes are decision boundaries that help classify the d...
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Decision Trees
Introduction Classification is a two-step process, learning step and prediction step, in machine learning. In the learning step, the model is developed based on given training data. In the prediction step, the model is used to predict the response fo...
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Naive Bayes' Classifier
Introduction A Naive Bayes classifier is a supervised machine learning model that’s used for classification task. As a classifier, it is used in face recognition, weather prediction, medical diagnosis, news classification, spam filtering, etc. Naive ...
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Logistic Regression
Introduction Logistic Regression is a supervised machine learning algorithm used to classify a target variable based on one or more continuous or discrete predictor features. It is same as linear regression on the inside, only difference being, it us...
Aug 7, 20225 min read
Linear Regression
Introduction Linear Regression is a supervised machine learning algorithm which finds a best fit line between a dependent variable and one or more independent variables. This means that linear regression finds a linear relationship between dependent ...
Aug 7, 20225 min read
