Published inTDS ArchiveUnderstanding Diffusion Probabilistic Models (DPMs)Building, step by step, the reasoning that leads to DPMs.Dec 5, 20228Dec 5, 20228
Published inTDS ArchiveThe exploration-exploitation trade-off: intuitions and strategiesUnderstanding e-greedy, optimistic initialisation, UCB and Thompson sampling strategiesApr 18, 20211Apr 18, 20211
Published inTDS ArchiveA simple introduction to Machine LearningTowards Data Science introductory post about ML.Dec 23, 20192Dec 23, 20192
Published inTDS ArchiveUnderstanding Variational Autoencoders (VAEs)Building, step by step, the reasoning that leads to VAEs.Sep 24, 2019116Sep 24, 2019116
Published inTDS ArchiveBayesian inference problem, MCMC and variational inferenceOverview of the Bayesian inference problem in statistics.Jul 1, 201914Jul 1, 201914
Published inTDS ArchiveEnsemble methods: bagging, boosting and stackingUnderstanding the key concepts of ensemble learning.Apr 23, 201937Apr 23, 201937
Published inTDS ArchiveIntroduction to Markov chainsDefinitions, properties and PageRank example.Feb 24, 201913Feb 24, 201913
Published inTDS ArchiveUnderstanding Generative Adversarial Networks (GANs)Building, step by step, the reasoning that leads to GANs.Jan 7, 201943Jan 7, 201943
Published inTDS ArchiveA gentle journey from linear regression to neural networksSoft introduction to some Machine Learning and Deep Learning concepts.Dec 8, 20185Dec 8, 20185