Archive | Machine Learning Algorithms

Linear Regression Tutorial Using Gradient Descent for Machine Learning

Linear Regression Tutorial Using Gradient Descent for Machine Learning

Stochastic Gradient Descent is an important and widely used algorithm in machine learning. In this post you will discover how to use Stochastic Gradient Descent to learn the coefficients for a simple linear regression model by minimizing the error on a training dataset. After reading this post you will know: The form of the Simple […]

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Overfitting and Underfitting With Machine Learning Algorithms

Overfitting and Underfitting With Machine Learning Algorithms

The cause of poor performance in machine learning is either overfitting or underfitting the data. In this post, you will discover the concept of generalization in machine learning and the problems of overfitting and underfitting that go along with it. Let’s get started. Approximate a Target Function in Machine Learning Supervised machine learning is best understood as […]

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Gentle Introduction to the Bias-Variance Trade-Off in Machine Learning

Gentle Introduction to the Bias-Variance Trade-Off in Machine Learning

Supervised machine learning algorithms can best be understood through the lens of the bias-variance trade-off. In this post, you will discover the Bias-Variance Trade-Off and how to use it to better understand machine learning algorithms and get better performance on your data. Let’s get started. Update Oct/2019: Removed discussion of parametric/nonparametric models (thanks Alex). Overview […]

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Supervised and Unsupervised Machine Learning Algorithms

Supervised and Unsupervised Machine Learning Algorithms

What is supervised machine learning and how does it relate to unsupervised machine learning? In this post you will discover supervised learning, unsupervised learning and semi-supervised learning. After reading this post you will know: About the classification and regression supervised learning problems. About the clustering and association unsupervised learning problems. Example algorithms used for supervised and […]

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Parametric and Nonparametric Machine Learning Algorithms

Parametric and Nonparametric Machine Learning Algorithms

What is a parametric machine learning algorithm and how is it different from a nonparametric machine learning algorithm? In this post you will discover the difference between parametric and nonparametric machine learning algorithms. Let’s get started. Learning a Function Machine learning can be summarized as learning a function (f) that maps input variables (X) to output […]

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How Machine Learning Algorithms Work

How Machine Learning Algorithms Work (they learn a mapping of input to output)

How do machine learning algorithms work? There is a common principle that underlies all supervised machine learning algorithms for predictive modeling. In this post you will discover how machine learning algorithms actually work by understanding the common principle that underlies all algorithms. Le’s get started. Let’s get started. Learning a Function Machine learning algorithms are […]

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Machine Learning Theory

5 Ways To Understand Machine Learning Algorithms (without math)

Where does theory fit into a top-down approach to studying machine learning? In the traditional approach to teaching machine learning, theory comes first requiring an extensive background in mathematics to be able to understand it. In my approach to teaching machine learning, I start with teaching you how to work problems end-to-end and deliver results. […]

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