Much of machine learning involves estimating the performance of a machine learning algorithm on unseen data. Confidence intervals are a way of quantifying the uncertainty of an estimate. They can be used to add a bounds or likelihood on a population parameter, such as a mean, estimated from a sample of independent observations from the […]
Cross-validation is a statistical method used to estimate the skill of machine learning models. It is commonly used in applied machine learning to compare and select a model for a given predictive modeling problem because it is easy to understand, easy to implement, and results in skill estimates that generally have a lower bias than […]
Statistical methods are used at each step in an applied machine learning project. This means it is important to have a strong grasp of the fundamentals of the key findings from statistics and a working knowledge of relevant statistical methods. Unfortunately, statistics is not covered in many computer science and software engineering degree programs. Even […]
A How are “Big Data” and “Machine Learning” related? Machine learning is a subfield of computer science and artificial intelligence concerned with developing systems that learn from experience. You can learn more about the definition of machine learning in this post: What is Machine Learning? When most people talk about machine learning, they really mean […]
A How are “Data Science” and “Machine Learning” related? Machine learning is a subfield of computer science and artificial intelligence concerned with developing systems that learn from experience. You can learn more about the definition of machine learning in this post: What is Machine Learning? When most people talk about machine learning, they really mean […]
A Why did you create this website? I started this site for two reasons: 1) I think machine learning is endlessly interesting. I’ve studied and worked in a few different areas of artificial intelligence, computational intelligence, multi-agent systems, severe weather forecasting, but I keep coming back to applied machine learning. 2) I want to help […]
A What is your background? Thanks for your interest. I have a bunch of degrees in computer science and artificial intelligence and I have worked many years in the tech industry in teams where your code has to work and be maintainable. If you want to see a detailed resume, I have a version on LinkedIn: […]
So, you’re working on a machine learning problem. I want to really nail down where you’re at right now. Let me make some guesses… 1) You Have a Problem So you have a problem that you need to solve. Maybe it’s your problem, an idea you have, a question, or something you want to address. […]
Machine learning is a large and interdisciplinary field of study. You can achieve impressive results with machine learning and find solutions to very challenging problems. But this is only a small corner of the broader field of machine learning often called predictive modeling or predictive analytics. In this post, you will discover how to change […]
Matrices that contain mostly zero values are called sparse, distinct from matrices where most of the values are non-zero, called dense. Large sparse matrices are common in general and especially in applied machine learning, such as in data that contains counts, data encodings that map categories to counts, and even in whole subfields of machine […]
