You need standard datasets to practice machine learning. In this short post you will discover how you can load standard classification and regression datasets in R. This post will show you 3 R libraries that you can use to load standard datasets and 10 specific datasets that you can use for machine learning in R. […]
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 […]
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 […]
What algorithm should you use on your dataset? This is the most common question in applied machine learning. It’s a question that can only be answered by trial and error, or what I call: spot-checking algorithms. In this post you will discover how to spot check algorithms on a dataset using R. Including the selection of […]
How do you choose the best algorithm for your dataset? Machine learning is a problem of induction where general rules are learned from specific observed data from the domain. It infeasible (impossible?) to know what representation or what algorithm to use to best learn from the data on a specific problem before hand, without knowing the […]
Where do you begin in machine learning? Is actually breaking ground and getting started a question of motivation? In this post discover the personal story of how finding the landmarks in machine learning made the difference for one software engineer. I received an inspiring email from Cliff Bryant in the new year. Cliff is a senior software engineer looking […]
What are the basic concepts in machine learning? I found that the best way to discover and get a handle on the basic concepts in machine learning is to review the introduction chapters to machine learning textbooks and to watch the videos from the first model in online courses. Pedro Domingos is a lecturer and professor on machine […]
When you’re an absolute beginner it can be very confusing. Frustratingly so. Even ideas that seem so simple in retrospect are alien when you first encounter them. There’s a whole new language to learn. I recently received this question: So using the iris exercise as an example if I were to pluck a flower from my […]
How do you get accurate results using machine learning on problem after problem? The difficulty is that each problem is unique, requiring different data sources, features, algorithms, algorithm configurations and on and on. The solution is to use a checklist that guarantees a good result every time. In this post you will discover a checklist […]
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 […]
