# Search results for "Probability Statistics"

## Naive Bayes for Machine Learning

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 […]

## Deep Learning Books

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 […]

## Linear Discriminant Analysis for Machine Learning

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 Tutorial for Machine Learning

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: […]

## Logistic Regression for Machine Learning

Logistic regression is another technique borrowed by machine learning from the field of statistics. It is the go-to method for binary classification problems (problems with two class values). In this post you will discover the logistic regression algorithm for machine learning. After reading this post you will know: The many names and terms used when […]

## Do Not Use Random Guessing As Your Baseline Classifier

I recently received the following question via email: Hi Jason, quick question. A case of class imbalance: 90 cases of thumbs up 10 cases of thumbs down. How would we calculate random guessing accuracy in this case? We can answer this question using some basic probability (I opened excel and typed in some numbers). Let’s […]

## Master Machine Learning Algorithms

Master Machine Learning Algorithms Finally Pull Back The Curtain And See How They Work With Clear Descriptions, Step-By-Step Tutorials and Working Examples in Spreadsheets You Learn Best By Implementing Algorithms From Scratch…But You Need Help With The First Step: The Math Developers Learn Fast By Trying Things Out… I’m a developer and I feel like I don’t […]

## Your First Machine Learning Project in R Step-By-Step

Do you want to do machine learning using R, but you’re having trouble getting started? In this post you will complete your first machine learning project using R. In this step-by-step tutorial you will: Download and install R and get the most useful package for machine learning in R. Load a dataset and understand it’s structure using statistical summaries […]

## Data Science From Scratch: Book Review

Programmers learn by implementing techniques from scratch. It is a type of learning that is perhaps slower than other types of learning, but fuller in that all of the micro decisions involved become intimate. The implementation is owned from head to tail. In this post we take a close look at Joel Grus popular book […]

## 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. […]