Joseph RoccainTowards Data ScienceUnderstanding Diffusion Probabilistic Models (DPMs)Building, step by step, the reasoning that leads to DPMs.23 min read·Dec 5, 2022--8--8
Joseph RoccainTowards Data ScienceThe exploration-exploitation trade-off: intuitions and strategiesUnderstanding e-greedy, optimistic initialisation, UCB and Thompson sampling strategies28 min read·Apr 18, 2021--1--1
Joseph RoccainTowards Data ScienceA simple introduction to Machine LearningTowards Data Science introductory post about ML.6 min read·Dec 23, 2019--2--2
Joseph RoccainTowards Data ScienceUnderstanding Variational Autoencoders (VAEs)Building, step by step, the reasoning that leads to VAEs.23 min read·Sep 24, 2019--114--114
Joseph RoccainTowards Data ScienceBayesian inference problem, MCMC and variational inferenceOverview of the Bayesian inference problem in statistics.17 min read·Jul 1, 2019--14--14
Joseph RoccainTowards Data ScienceEnsemble methods: bagging, boosting and stackingUnderstanding the key concepts of ensemble learning.20 min read·Apr 23, 2019--34--34
Joseph RoccainTowards Data ScienceIntroduction to Markov chainsDefinitions, properties and PageRank example.19 min read·Feb 24, 2019--13--13
Joseph RoccainTowards Data ScienceUnderstanding Generative Adversarial Networks (GANs)Building, step by step, the reasoning that leads to GANs.20 min read·Jan 7, 2019--42--42
Joseph RoccainTowards Data ScienceA gentle journey from linear regression to neural networksSoft introduction to some Machine Learning and Deep Learning concepts.25 min read·Dec 8, 2018--5--5