contents advantages and limitations of decision trees bootstrap aggregation random forests boosting exercises deep learning introduction feed-forward neural networks back-propagation methods for training steepest descent levenberg-marquardt method limited-memory bfgs method adaptive gradient methods examples in python simple polynomial regression image classification exercises linear algebra and functional analysis vector spacesbasesand matrices inner product complex vectors and matrices orthogonal projections eigenvalues and eigenvectors leftand right-eigenvectors matrix decompositions ( )lu decomposition woodbury identity cholesky decomposition qr decomposition and the gram-schmidt procedure singular value decomposition solving structured matrix equations functional analysis fourier transforms discrete fourier transform fast fourier transform multivariate differentiation and optimization multivariate differentiation taylor expansion chain rule optimization theory convexity and optimization lagrangian method duality