# Tag: Linear regression

### Gradient Descent for Linear Regression

- Naveen
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Gradient Descent is defined as one of the most commonly used iterative optimization algorithm of machine learning to train the machine learning and deep learning models. It helps in finding the local minima of a function. The best way to define the local minima or local maxima of a function using gradient descent is as…

Read More### Linear Regression for Machine Learning

- Naveen
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Linear regression is the statistical technique to find relationship between two or more variables. To predict the values of response (target) variable based on that values of predictors (external / independent variables) we can use linear regression. Simple linear regression is having only one external factor while Multiple liner regression is having more than one…

Read More### Difference between Linear Regression and Logistic Regression?

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Linear regression and logistic regression are two of the most commonly used statistical techniques in machine learning and data analysis. Although both methods are used to predict outcomes, they differ fundamentally in their implementation and assumptions. In this article, we discuss the differences between linear and logistic regression. What is regression? Regression analysis is a…

Read More### Important Supervised and Unsupervised Algorithms for Machine Learning

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Machine learning is a branch of computer science and artificial intelligence that allows machines to learn automatically without special programming. It involves using algorithms and statistical models to analyze and interpret data and make predictions based on that analysis. Machine learning can be broadly divided into two types of algorithms: supervised and unsupervised. In this…

Read More### What is Supervised Learning?

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Supervised learning is a type of machine learning where a computer is taught using examples of real data and “known” data, where the teacher knows the correct answer and teaches someone else. Learning can take any form, from simple human feedback or input to a more complex model that predicts the outcome of future events.…

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