Over the course of the last two and a half years, I have written over one hundred posts for my blog “Learning Machines” on the topics of data science, i.e. statistics, artificial intelligence, machine learning, and deep learning.
I use many of those in my university classes and in this post, I will give you the first part of a learning path for the knowledge that has accumulated on this blog over the years to become a well-rounded data scientist, so read on!
Continue reading “Learning Path for “Data Science with R” – Part I”
More and more decisions by banks on who gets a loan are being made by artificial intelligence. The terms being used are credit scoring and credit decisioning.
They base their decisions on models whether the customer will pay back the loan or will default, i.e. determine their creditworthiness. If you want to learn how to build such a model in R yourself (with the latest R ≥ 4.1.0 syntax as a bonus), read on!
Continue reading “Will I get my Money back? Credit Scoring with OneR”
This is our 101’st blog post here on Learning Machines and we have prepared something very special for you!
Oftentimes the different concepts of data science, namely artificial intelligence (AI), machine learning (ML), and deep learning (DL) are confused… so we asked the most advanced AI in the world, OpenAI GPT-3, to write a guest post for us to provide some clarification on their definitions and how they are related.
We are most delighted to present this very impressive (and only slightly redacted) essay to you – enjoy!
Continue reading “The Most Advanced AI in the World explains what AI, Machine Learning, and Deep Learning are!”
In 2018 the renowned scientific journal science broke a story that researchers had re-engineered the commercial criminal risk assessment software COMPAS with a simple logistic regression (Science: The accuracy, fairness, and limits of predicting recidivism).
According to this article, COMPAS uses 137 features, the authors just used two. In this post, I will up the ante by showing you how to achieve similar results using just one simple rule based on only one feature which is found automatically in no-time by the
OneR package, so read on!
Continue reading “Recidivism: Identifying the Most Important Predictors for Re-offending with OneR”
During our little break, Valentine’s Day was celebrated. Yet for many, it was a depressing day because they are single and are looking for love.
Speed dating is a popular format (in times of Covid-19 also in virtual form) to meet many different potential soul mates in a short period of time. If you want to learn which factors determine “getting to the next round”, read on!
Continue reading “Cupid’s Arrow: How to Boost your Chances at Speed Dating!”
The workhorse of Machine Learning is Gradient Descent. If you want to understand how and why it works and, along the way, want to learn how to plot and animate 3D-functions in R read on!
Continue reading “Why Gradient Descent Works (and How To Animate 3D-Functions in R)”
We already had a lot of examples that make use of the
OneR package (install free from CRAN), which can be found in the respective Category: OneR.
Here we will give you some concrete examples from the area of research on Type 2 Diabetes Mellitus (DM) to show that the package is especially well suited in the field of medical research, so read on!
Continue reading “OneR in Medical Research: Finding Leading Symptoms, Main Predictors and Cut-Off Points”
We already covered Neural Networks and Logistic Regression in this blog.
If you want to gain an even deeper understanding of the fascinating connection between those two popular machine learning techniques read on!
Continue reading “Logistic Regression as the Smallest Possible Neural Network”
Forecasting the future has always been one of man’s biggest desires and many approaches have been tried over the centuries. In this post we will look at a simple statistical method for time series analysis, called AR for Autoregressive Model. We will use this method to predict future sales data and will rebuild it to get a deeper understanding of how this method works, so read on!
Continue reading “Time Series Analysis: Forecasting Sales Data with Autoregressive (AR) Models”
We all know the classical Sci-Fi trope of intelligent machines becoming conscious and all the potential ramifications that could follow from there (free will, fighting their human creators, ethical dilemmas, and so forth). Now, is this a realistic scenario? As a researcher in the area of AI (see e.g. So, what is AI really?), with a penchant for philosophy, I share my thoughts here with you, so read on!
Continue reading “Will AI become conscious any time soon?”