Frederik vom LehnUnderstanding TransformersThe underlying deep learning architecture for ChatGPT and new vision models.May 29May 29
Frederik vom LehnWord Embeddings and their BiasExplaining the paper: Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings [1].Jan 9Jan 9
Frederik vom LehnOptimising ML InferenceHow to improve latency during inference in Machine Learning!Nov 15, 20231Nov 15, 20231
Frederik vom LehnUnderstanding Vector Similarity for Machine LearningCosine Similarity, Dot Product, Manhattan Distance L1, Euclidian Distance L2.Oct 7, 20232Oct 7, 20232
Frederik vom LehnUnderstanding Bias and Variance in Machine LearningThe terms bias and variance describe how well the model fits the actual unknown data distribution. In general one never has a dataset that…Sep 15, 2023Sep 15, 2023
Frederik vom LehnComplete Guide to Neural NetworksBased on a given dataset, a neuronal network creates a function f which maps the relationship between features Xi and labels Y. The…Aug 18, 20233Aug 18, 20233
Frederik vom LehnUnderstanding the Convolutional Filter Operation in CNN’s.Aug 18, 20235Aug 18, 20235
Frederik vom LehnUnderstanding the Structure of RGB Images and How Pixel Values Represent ColorThis article explains how RGB images are represented as matrices and how a single pixel value represents colour.Aug 18, 20231Aug 18, 20231