Support Vector Machines are perhaps one of the most popular and talked about machine learning algorithms. They were extremely popular around the time they were developed in the 1990s and continue to be the go-to method for a high-performing algorithm with little tuning. In this post you will discover the Support Vector Machine (SVM) machine […]
A downside of K-Nearest Neighbors is that you need to hang on to your entire training dataset. The Learning Vector Quantization algorithm (or LVQ for short) is an artificial neural network algorithm that lets you choose how many training instances to hang onto and learns exactly what those instances should look like. In this post […]
In this post you will discover the k-Nearest Neighbors (KNN) algorithm for classification and regression. After reading this post you will know. The model representation used by KNN. How a model is learned using KNN (hint, it’s not). How to make predictions using KNN The many names for KNN including how different fields refer to […]
There are so many deep learning libraries to choose from. Which are the good professional libraries that are worth learning and which are someones side project and should be avoided. It is hard to tell the difference. In this post you will discover the top deep learning libraries that you should consider learning and using […]
Naive Bayes is a very simple classification algorithm that makes some strong assumptions about the independence of each input variable. Nevertheless, it has been shown to be effective in a large number of problem domains. In this post you will discover the Naive Bayes algorithm for categorical data. After reading this post, you will know. How […]
Naive Bayes is a simple but surprisingly powerful algorithm for predictive modeling. In this post you will discover the Naive Bayes algorithm for classification. After reading this post, you will know: The representation used by naive Bayes that is actually stored when a model is written to a file. How a learned model can be […]
Decision Trees are an important type of algorithm for predictive modeling machine learning. The classical decision tree algorithms have been around for decades and modern variations like random forest are among the most powerful techniques available. In this post you will discover the humble decision tree algorithm known by it’s more modern name CART which stands […]
There are not many books on deep learning at the moment because it is such a young area of study. There are a few books available though and some very interesting books in the pipeline that you can purchase by early access. In this post, you will discover the books available right now on deep […]
Logistic regression is a classification algorithm traditionally limited to only two-class classification problems. If you have more than two classes then Linear Discriminant Analysis is the preferred linear classification technique. In this post you will discover the Linear Discriminant Analysis (LDA) algorithm for classification predictive modeling problems. After reading this post you will know: The […]
Logistic regression is one of the most popular machine learning algorithms for binary classification. This is because it is a simple algorithm that performs very well on a wide range of problems. In this post you are going to discover the logistic regression algorithm for binary classification, step-by-step. After reading this post you will know: […]
