# Search results for "Model Risk"

## How to Reframe Your Time Series Forecasting Problem

You do not have to model your time series forecast problem as-is. There are many ways to reframe your forecast problem that can both simplify the prediction problem and potentially expose more or different information to be modeled. A reframing can ultimately result in better and/or more robust forecasts. In this tutorial, you will discover […]

## How to Configure the Gradient Boosting Algorithm

Gradient boosting is one of the most powerful techniques for applied machine learning and as such is quickly becoming one of the most popular. But how do you configure gradient boosting on your problem? In this post you will discover how you can configure gradient boosting on your machine learning problem by looking at configurations […]

## Data Leakage in Machine Learning

Data leakage is a big problem in machine learning when developing predictive models. Data leakage is when information from outside the training dataset is used to create the model. In this post you will discover the problem of data leakage in predictive modeling. After reading this post you will know: What is data leakage is […]

## Parametric and Nonparametric Machine Learning Algorithms

What is a parametric machine learning algorithm and how is it different from a nonparametric machine learning algorithm? In this post you will discover the difference between parametric and nonparametric machine learning algorithms. Let’s get started. Learning a Function Machine learning can be summarized as learning a function (f) that maps input variables (X) to output […]

## Review of Machine Learning With R

How do you get started with machine learning in R? In this post you will discover the book Machine Learning with R by Brett Lantz that has the goal of telling you exactly how to get started practicing machine learning in R. We cover the audience for the book, a nice deep breakdown of the […]

## Tune Machine Learning Algorithms in R (random forest case study)

It is difficult to find a good machine learning algorithm for your problem. But once you do, how do you get the best performance out of it. In this post you will discover three ways that you can tune the parameters of a machine learning algorithm in R. Walk through a real example step-by-step with […]

## Basic Concepts in Machine Learning

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 […]

## Get Your Dream Job in Machine Learning by Delivering Results

You can rise up and take on your desire to become an a machine learning practitioner and data scientist. You have to work hard, learn the skills and demonstrate that you can deliver results, but you don’t need a fancy degree or a fancy background. In this post I want to demonstrate that this is […]

## Building a Production Machine Learning Infrastructure

Midwest.io is was a conference in Kansas City on July 14-15 2014. At the conference, Josh Wills gave a talk on what it takes to build production machine learning infrastructure in a talk titled “From the lab to the factory: Building a Production Machine Learning Infrastructure“. Josh Wills is a the Senior Director of Data […]

## Master Kaggle By Competing Consistently

How do you get good at Kaggle competitions? It is a common question I get asked. The best advice for getting started and getting good is to consistently participate in competitions. You cannot help but get better at machine learning. A recent post by Triskelion titled “Reflecting back on one year of Kaggle contests” bares […]