Ensembles can give you a boost in accuracy on your dataset. In this post you will discover how you can create some of the most powerful types of ensembles in Python using scikit-learn. This case study will step you through Boosting, Bagging and Majority Voting and show you how you can continue to ratchet up […]
From Developer to Machine Learning Practitioner in 14 Days In this mini-course you will discover how you can get started, build accurate models and confidently complete predictive modeling machine learning projects using R in 14 days. This is a big and important post. You might want to bookmark it. Let’s get started. Who Is This […]
How do you compare the estimated accuracy of different machine learning algorithms effectively? In this post you will discover 8 techniques that you can use to compare machine learning algorithms in R. You can use these techniques to choose the most accurate model, and be able to comment on the statistical significance and the absolute […]
Ensembles can give you a boost in accuracy on your dataset. In this post you will discover how you can create three of the most powerful types of ensembles in R. This case study will step you through Boosting, Bagging and Stacking and show you how you can continue to ratchet up the accuracy of […]
There are a ton of packages for R. Which ones are best to use for your machine learning project? In this post you will discover the exact R functions and packages recommended for each sub task in a machine learning journey. This is useful. Bookmark this page. I’m sure you will be checking back time […]
Do you want some tips and tricks that are useful in developing successful machine learning applications? This is the subject of a journal article from 2012 titled “A Few Useful Things to Know about Machine Learning” (PDF) by University of Washing professor Pedro Domingos. It’s an in interesting read with a great opening hook: developing successful machine […]
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 […]
Machine Learning has been commoditized into a service. This is a recent trend that looks like it will develop into the mainstream like commoditized storage and virtualization. It is the natural next step. In this review you will learn about BigML that provides commoditized machine learning as a service for business analysts and application integration. […]
Weka is the perfect platform for studying machine learning. It provides a graphical user interface for exploring and experimenting with machine learning algorithms on datasets, without you having to worry about the mathematics or the programming. In a previous post we looked at how to design and run an experiment running 3 algorithms on a […]
Having one or two algorithms that perform reasonably well on a problem is a good start, but sometimes you may be incentivised to get the best result you can given the time and resources you have available. In this post, you will review methods you can use to squeeze out extra performance and improve the […]
