Joseph RoccainTowards Data ScienceUnderstanding Diffusion Probabilistic Models (DPMs)Building, step by step, the reasoning that leads to DPMs.Dec 5, 20228Dec 5, 20228

Joseph RoccainTowards Data ScienceThe exploration-exploitation trade-off: intuitions and strategiesUnderstanding e-greedy, optimistic initialisation, UCB and Thompson sampling strategiesApr 18, 20211Apr 18, 20211

Joseph RoccainTowards Data ScienceA simple introduction to Machine LearningTowards Data Science introductory post about ML.Dec 23, 20192Dec 23, 20192

Joseph RoccainTowards Data ScienceUnderstanding Variational Autoencoders (VAEs)Building, step by step, the reasoning that leads to VAEs.Sep 24, 2019116Sep 24, 2019116

Joseph RoccainTowards Data ScienceBayesian inference problem, MCMC and variational inferenceOverview of the Bayesian inference problem in statistics.Jul 1, 201914Jul 1, 201914

Joseph RoccainTowards Data ScienceEnsemble methods: bagging, boosting and stackingUnderstanding the key concepts of ensemble learning.Apr 23, 201936Apr 23, 201936

Joseph RoccainTowards Data ScienceIntroduction to Markov chainsDefinitions, properties and PageRank example.Feb 24, 201913Feb 24, 201913

Joseph RoccainTowards Data ScienceUnderstanding Generative Adversarial Networks (GANs)Building, step by step, the reasoning that leads to GANs.Jan 7, 201942Jan 7, 201942

Joseph RoccainTowards Data ScienceA gentle journey from linear regression to neural networksSoft introduction to some Machine Learning and Deep Learning concepts.Dec 8, 20185Dec 8, 20185