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By: Sergios Theodoridis
Technology
Title: SOLUTIONS MANUAL for Machine Learning; A Bayesian and Optimization Perspective 2nd Edition By Sergios Theodoridis - Complete Elaborated & Latest. ALL Chapters (1-19) Included & Updated #MachineLearning #BayesianInference #OptimizationTheory #StochasticProcesses #DeepLearning #NeuralNetworks #GradientDescent #KernelMethods #SparsityAware #MonteCarloMethods #ProbabilisticModels #EMAlgorithm #DimensionalityReduction #LatentVariables #MLAlgorithms Chapter 1. Introduction Chapter 2. Probability and stochastic Processes Chapter 3. Learning in parametric Modeling: Basic Concepts and Directions Chapter 4. Mean-Square Error Linear Estimation Chapter 5. Stochastic Gradient Descent: the LMS Algorithm and its Family Chapter 6. The Least-Squares Family Chapter 7. Classification: A Tour of the Classics Chapter 8. Parameter Learning: A Convex Analytic Path Chapter 9. Sparsity-Aware Learning: Concepts and Theoretical Foundations Chapter 10. Sparsity-Aware Learning: Algorithms and Applications Chapter 11. Learning in Reproducing Kernel Hilbert Spaces Chapter 12. Bayesian Learning: Inference and the EM Algorithm Chapter 13. Bayesian Learning: Approximate Inference and nonparametric Models Chapter 14. Montel Carlo Methods Chapter 15. Probabilistic Graphical Models: Part 1 Chapter 16. Probabilistic Graphical Models: Part 2 Chapter 17. Particle Filtering Chapter 18. Neural Networks and Deep Learning Chapter 19. Dimensionality Reduction and Latent Variables Modeling Title: SOLUTIONS MANUAL for Machine Learning; A Bayesian and Optimization Perspective 2nd Edition By Sergios Theodoridis - Complete Elaborated & Latest. ALL Chapters (1-19) Included & Updated
Price: $36.00