If you don’t know what algorithm to use on your problem, try a few. Alternatively, you could just try Random Forest and maybe a Gaussian SVM. In a recent study these two algorithms were demonstrated to be the most effective when raced against nearly 200 other algorithms averaged over more than 100 data sets. In […]
Naive Bayes is a simple and powerful technique that you should be testing and using on your classification problems. It is simple to understand, gives good results and is fast to build a model and make predictions. For these reasons alone you should take a closer look at the algorithm. In a recent blog post, you […]
Any book on machine learning will list and describe dozens of machine learning algorithms. Once you start using tools and libraries you will discover dozens more. This can really wear you down, if you think you need to know about every possible algorithm out there. A simple trick to tackle this feeling and take some […]
Edward Raff is the author of the Java Machine Learning library called JSAT (which is an acronym for Java Statistical Analysis Tool). Edward has implemented many algorithms in creating this library and I recently reached out to him and asked what advice he could give to beginners implementing machine learning algorithms from scratch. In this post […]
Machine learning algorithms are complex systems that require study to understand. Static descriptions of machine learning algorithms are a good starting point, but are insufficient to get a feeling for how the algorithm behaves. You need to see the algorithm in action. Experimenting on a running machine learning algorithms will allow you to build an […]
Algorithms are a big part of the field of machine learning. You need to understand what algorithms are out there, and how to use them effectively. An easy way to shortcut this knowledge is to review what is already known about an algorithm, to research it. In this post you will discover the importance of […]
Algorithms make up a big part of machine learning. You select and apply machine learning algorithms to build a model from your data, select features, combine the predictions from multiple models and even evaluate the capabilities of a given model. In this post you will review 5 different approaches that you can use to study […]
Machine learning algorithms are complex. To get good at applying a given algorithm you need to study it from multiple perspectives: algorithmic, mathematical and empirical. It’s this last point I want to stress. You need to build up an intuition or how an algorithm behaves on real data. You need to work on lots of […]
Machine Learning can be difficult to understand when getting started. There are a lot of algorithms and processes that are prescribed and used, many with difficult to penetrate explanations for how and why the work. It can feel overwhelming. An approach that you can use to get handle on machine learning algorithms and practices is […]
What is the best machine learning algorithm? I get this question a lot. Maybe even daily. Sometimes it’s a general question. I figure people want to make sure they are learning the one true machine learning algorithm and not wasting their time on anything less. Most other times it is with regard to a specific […]
