Spot-checking is a way of discovering which algorithms perform well on your machine learning problem. You cannot know which algorithms are best suited to your problem before hand. You must trial a number of methods and focus attention on those that prove themselves the most promising. In this post you will discover 6 machine learning […]
Machine learning algorithms are a very large part of machine learning. You have to understand how they work to make any progress in the field. In this post you will discover a 14-part machine learning algorithms mini course that you can follow to finally understand machine learning algorithms. We are going to cover a lot […]
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 […]
How can you learn about a machine learning tool quickly? Using the right tool can mean the difference between getting good predictions quickly and a project on which you cannot deliver. You need to evaluate machine learning tools before you use them. You need to know that a machine learning tool is right for you, right […]
It is valuable to get insight into how real people are getting started in machine learning. In this post you will discover how a beginner (just like you) got started and is making great progress in applying machine learning. I find interviews like this absolutely fascinating because of all of the things you can learn. […]
Implementing machine learning algorithms from scratch seems like a great way for a programmer to understand machine learning. And maybe it is. But there some downsides to this approach too. In this post you will discover some great resources that you can use to implement machine learning algorithms from scratch. You will also discover some of […]
Has this happened to you? You are working on your dataset. You create a classification model and get 90% accuracy immediately. “Fantastic” you think. You dive a little deeper and discover that 90% of the data belongs to one class. Damn! This is an example of an imbalanced dataset and the frustrating results it can […]
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 […]
The book Applied Predictive Modeling teaches practical machine learning theory with code examples in R. It is an excellent book and highly recommended to machine learning practitioners and users of R for machine learning. In this post you will discover the benefits of this book and how it can help you become a better machine […]
Jeremy Howard, formally of Kaggle gave a presentation at the University of San Francisco in mid 2013. In that presentation he touched on some of the broader benefits of machine learning competitions like those held on Kaggle. In this post you will discover 5 points I extracted from this talk that will motivate you to […]
