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Bayesian Methods for Machine Learning As part of this Coursera spetialization we implemented different algorithms like: Expectation maximization for Gaussian Mixture Models (GMMs) Applied Variational Inference in a Variational AutoEncoder (VAE) architecture using Convolutional Networks Coursera gives you opportunities to learn about Bayesian statistics and related concepts in data science and machine learning through courses and Specializations from top-ranked schools like Duke University, the University of California, Santa Cruz, and the National Research University Higher School of Economics in Russia. This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods. People apply Bayesian methods in many areas: from game development to drug discovery. 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The things you’ll learn in this course are not only applicable to A/B testing, but rather, we’re using A/B testing as a concrete example of how Bayesian techniques can be applied. The result is a powerful, consistent framework for approaching many problems that arise in machine learning, including parameter estimation, model comparison, and decision making. They give superpowers to many machine learning algorithms: handling missing data, extracting much more information from small datasets. Coursera Webpage. Bayesian Methods for Machine Learning 4. Bayesian probability allows us to model and reason about all types of uncertainty. Download Tutorial Bayesian Methods for Machine Learning. They give superpowers to many machine learning algorithms: handling missing data, extracting much … Absolutely. Introduction to Deep Learning 2. How to Win a Data Science Competition: Learn from Top Kagglers 3. 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Coursera gives you opportunities to learn about Bayesian statistics and related concepts in data science and machine learning through courses and Specializations from top-ranked schools like Duke University, the University of California, Santa Cruz, and the National Research University Higher School of Economics in Russia. It covers some advanced topics such as Latent Dirichlet Allocation, Variational Autoencoders and Gaussian Processes. Bayesian Methods for Machine Learning. Coursera gives you opportunities to learn about Bayesian statistics and related concepts in data science and machine learning through courses and Specializations from top-ranked schools like Duke University, the University of California, Santa Cruz, and the National Research University Higher School of Economics in Russia. 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Coursera gives you opportunities to learn about Bayesian statistics and related concepts in data science and machine learning through courses and Specializations from top-ranked schools like Duke University, the University of California, Santa Cruz, and the National Research University Higher School of Economics in Russia. If you want ideas you can try Hidden Markov Model or state base models. Description.