The universal recommender in Action(ML)
04/19/21
This article presents a new collaborative filtering technique. The universal recommender can be run as “engine” of ActionML's Harness. Read more
19 Search Results for Data Science
Thinking AI means re-thinking data
05/28/20
While doing AI is sexy and cool, data infrastructure is not considered any of this, even though machine learning applications rely on it. Read more
Evaluating machine learning models: The issue with test data sets
04/21/20
By using a representative test set and various metrics, machine learning models can be evaluated and compared. Read more
Evaluating machine learning models: How to tackle metrics
09/06/19
Once a model has been trained, it can be evaluated in different ways and with more or less complex and meaningful procedures and machine learning metrics. Read more
Hands-on Spark intro: Cross Join customers and products with business logic
08/06/19
In this blog post, I want to share my aha moments with you I had during the development of my... Read more
Deploying a recommender system for the movie-lens dataset – Part 1
07/16/19
In this post I will discuss building a simple recommender system for a movie database which will suggest top movies and predict user votes. Read more
Assessing bias in search results
05/07/19
In this article, I describe the idea behind the retrievability metric which can be used to measure bias in search results. Read more
Can you win the stacking challenge? An example of heuristic optimization
03/27/19
How to use heuristic algorithms to solve complicated optimization problems: Can you win the stacking challenge? Read more
Machine learning: Moving from experiments to production
03/19/19
Join me as I go back to the drawing board and think about approaches to plan an ML pipeline that fits your organization’s needs. We'll look at goals, technical approaches and an example architecture. Read more