Published inTDS ArchiveUnderstanding Diffusion Probabilistic Models (DPMs)Building, step by step, the reasoning that leads to DPMs.Dec 5, 2022A response icon8Dec 5, 2022A response icon8
Published inTDS ArchiveThe exploration-exploitation trade-off: intuitions and strategiesUnderstanding e-greedy, optimistic initialisation, UCB and Thompson sampling strategiesApr 18, 2021A response icon1Apr 18, 2021A response icon1
Published inTDS ArchiveA simple introduction to Machine LearningTowards Data Science introductory post about ML.Dec 23, 2019A response icon2Dec 23, 2019A response icon2
Published inTDS ArchiveUnderstanding Variational Autoencoders (VAEs)Building, step by step, the reasoning that leads to VAEs.Sep 24, 2019A response icon116Sep 24, 2019A response icon116
Published inTDS ArchiveBayesian inference problem, MCMC and variational inferenceOverview of the Bayesian inference problem in statistics.Jul 1, 2019A response icon14Jul 1, 2019A response icon14
Published inTDS ArchiveEnsemble methods: bagging, boosting and stackingUnderstanding the key concepts of ensemble learning.Apr 23, 2019A response icon37Apr 23, 2019A response icon37
Published inTDS ArchiveIntroduction to Markov chainsDefinitions, properties and PageRank example.Feb 24, 2019A response icon13Feb 24, 2019A response icon13
Published inTDS ArchiveUnderstanding Generative Adversarial Networks (GANs)Building, step by step, the reasoning that leads to GANs.Jan 7, 2019A response icon43Jan 7, 2019A response icon43
Published inTDS ArchiveA gentle journey from linear regression to neural networksSoft introduction to some Machine Learning and Deep Learning concepts.Dec 8, 2018A response icon5Dec 8, 2018A response icon5