Christiaan DefauxAn overview of fraud/anomaly detection algorithms (machine learning and numerical methods)Outlier/Anomaly Detection for FraudOct 10, 2021Oct 10, 2021
Christiaan DefauxThe Sparse Autoencoder (SAE) for DummiesIf you’ve landed on this page, you’re probably familiar with a variety of deep neural network models. I will assume that you have a…Feb 5, 2020Feb 5, 2020
Christiaan DefauxPhi Coefficient A.K.A Matthews Correlation Coefficient (Binary Classification)In machine learning/data science, we often run into problems where we’re trying to classify binary (two-class) data. In this case, you…Jan 27, 2020Jan 27, 2020
Christiaan DefauxUnsupervised Learning: The autoencoder in laymans termsSometimes we might be presented with data that lack labels. This requires a special set of machine learning models under the umbrella of…Jan 22, 2020Jan 22, 2020
Christiaan DefauxKullback-Leibler Divergence for DummiesIf you’re diving deep into deep learning or machining a better grasp of machine learning then an understanding of the Kullback-Leibler…Jan 16, 2020Jan 16, 2020
Christiaan DefauxMusic Generation using Deep Learning — Design DecisionsThis post will be based mostly on information from Deep Learning Techniques for Music Generation — A Survey (Briot et al. 2019), which…Jan 8, 2020Jan 8, 2020
Christiaan DefauxUsing the Durbin-Watson (DW) test for time-series dataFirst of all, one must be aware of autocorrelation in order to appropriately apply the DW test. Autocorrelation, also known as serial…Aug 9, 2019Aug 9, 2019
Christiaan DefauxThe benefits of a growth mindset in data scienceI’m currently in a data science immersive, read intensive. It’s a lot of information to download into the trusty old biological hard drive…Aug 9, 2019Aug 9, 2019