Machine Learning Tutorial
Advantage of using Multinomial Logistic Regression
Introduction
One of the most common machine learning tasks is classification, which categorizes data into labels. Basic classification is binary classification, which has two classes....
Advantages and Disadvantages of Binary Logistic Regression
Introduction
Binary logistic regression is a popular machine learning approach for binary classification tasks. One or more predictor variables are used to predict the likelihood...
Advantages and Disadvantages of Gradient Boosting Machine
Machine learning is one of the most common technologies for developing prediction models for a variety of challenging regression and classification problems. Gradient Boosting...
Advantages and Disadvantages of Artificial Neural Network
Introduction to Artificial Neural Networks
Inspired by the neural structure and behavior of the human brain, artificial neural networks (ANNs) are among the most significant...
Stepwise Regression in Machine Learning & Types of it
What is Stepwise Regression Analysis?
A approach for selecting a selection of predictors(features) to incorporate into a regression model is stepwise regression in machine learning....
What is Softmax Activation Function in Machine Learning?
Machine learning, especially classification, relies on the softmax activation function. It is often utilized in neural network output layers for multi-class categorization. It converts...
What is Maximum Likelihood Estimation in Machine Learning?
Introduction to Maximum Likelihood Estimation
MLE is a prominent method for estimating statistical model parameters. It is essential in statistics and machine learning because it...
Gaussian Naïve Bayes Classifier in field of Machine Learning
Modern technology uses machine learning to solve challenges like spam filtering and sentiment analysis. The Naïve Bayes classifier, a fundamental machine learning method, excels...
What is Target Encoding in Machine Learning and When to use?
What is Target Encoding in Machine Learning?
Target encoding, often called mean encoding, is used in machine learning for categorical variables. Target encoding converts categorical...
What is Frequency Encoding? & Understanding it’s Advantages
Frequency Encoding Machine Learning
To enable model learning and generalization, preprocessing data is crucial in machine learning. A major problem during preprocessing is handling categorical...
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