Click to learn more about co-author Maarit Widmann. Click to learn more about co-author Anna Martin. Click to learn more about co-author Rosaria Silipo. Do you remember the Iron Chef battles? It was a televised series of cook-offs in which famous chefs rolled up their sleeves to compete in making the perfect dish. Based on a […]
Ensemble Models: Bagging and Boosting
Click to learn more about author Rosaria Silipo. Ensemble models combine multiple learning algorithms to improve the predictive performance of each algorithm alone. There are two main strategies to ensemble models — bagging and boosting — and many examples of predefined ensemble algorithms. Bootstrap aggregation, or bagging, is an ensemble meta-learning technique that trains many […]
Deploying the Obscure Python Script: Neuro-Styling of Portrait Pictures
Click to learn more about author Rosaria Silipo. Click to learn more about co-author Mykhailo Lisovyi. Today’s Style: Caravaggio or Picasso? While surfing on the internet a few months ago, we came across this study[i], promising to train a neural network to alter any image according to your preferred painter’s style. These kinds of studies […]
From a Single Decision Tree to a Random Forest
Click to learn more about author Rosaria Silipo. The co-author of this column was Kathrin Melcher. Decision trees are a set of very popular supervised classification algorithms. They are very popular for a few reasons: They perform quite well on classification problems, the decisional path is relatively easy to interpret, and the algorithm to build […]
The 80/20 Challenge: From Classic to Innovative Data Science Projects
Click to learn more about author Rosaria Silipo. Sometimes when you talk to data scientists, you get this vibe as if you’re talking to priests of an ancient religion. Obscure formulas, complex algorithms, a slang for the initiated, and on top of that, some new required script. If you get these vibes for all projects, […]
Automated Machine Learning: Just How Much?
Click to learn more about author Rosaria Silipo. An interview with three data scientists and guided automation experts There is currently a lot of talk about automated machine learning. There is also a high level of skepticism. I am here with data scientists Paolo Tamagnini, Simon Schmid and Christian Dietz.. to ask a few questions […]
Fraud Detection Using a Neural Autoencoder
Click to learn more about author Rosaria Silipo. The co-authors of this column were Kathrin Melcher and Maarit Widmann. The Fraud Detection Problem Fraud detection belongs to the more general class of problems — the anomaly detection. Anomaly is a generic, not domain-specific, concept. It refers to any exceptional or unexpected event in the data, […]
Neural Machine Translation with Sequence to Sequence RNN
Click to learn more about author Rosaria Silipo. The co-authors of this column were Kathrin Melcher and Simon Schmid Automatic machine translation has been a popular subject for machine learning algorithms. After all, if machines can detect topics and understand texts, translation should be just the next step. Machine translation can be seen as a […]
Data Dimensionality Reduction in the Age of Machine Learning
Click to learn more about author Rosaria Silipo. Machine Learning is all the rage as companies try to make sense of the mountains of data they are collecting. Data is everywhere and proliferating at unprecedented speed. But, more data is not always better. In fact, large amounts of data can not only considerably slow down […]
Practicing Data Science
Click to learn more about author Rosaria Silipo. There are many declinations of Data Science projects: with or without labeled data; stopping at data wrangling or involving Machine Learning algorithms; predicting classes or predicting numbers; with unevenly distributed classes, with binary classes, or even with no examples at all of one of the classes; with […]