 Home | Amazing | Today | Tags | Publishers | Years | Account | Search     R Deep Learning Essentials

#### Key Features

• Harness the ability to build algorithms for unsupervised data using deep learning concepts with R
• Master the common problems faced such as overfitting of data, anomalous datasets, image recognition, and performance tuning while building the models
• Build models relating to neural...  Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute...  Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems.

#### Key Features

• Explore deep reinforcement learning (RL), from the first principles to the latest algorithms
• Evaluate high-profile RL methods, including value...  Mathematics for Electrical Engineering and ComputingMathematics for Electrical Engineering and Computing embraces many applications of modern mathematics, such as Boolean Algebra and Sets and Functions, and also teaches both discrete and continuous systems - particularly vital for Digital Signal Processing (DSP). In addition, as most modern engineers are required to study software,...   Ordinary Differential EquationsSkillfully organized introductory text examines origin of differential equations, then defines basic terms and outlines general solution of a differential equation. Subsequent sections deal with integrating factors; dilution and accretion problems; linearization of first order systems; Laplace Transforms; Newton’s Interpolation Formulas,...   Partial Differential Equation Analysis in Biomedical Engineering: Case Studies with Matlab Aimed at graduates and researchers, and requiring only a basic knowledge of multi-variable calculus, this introduction to computer-based partial differential equation (PDE) modeling provides readers with the practical methods necessary to develop and use PDE mathematical models in biomedical engineering. Taking an applied approach, rather...  Probability and Schrodinger's Mechanics The presentation and interpretation of (non-relativistic) quantum mechanics is a very well-worked area of study; there have to be very good reasons for adding to the literature on this subject. My reasons are (obviously) that I am far from satisfied with much of the published work and find difficulties with some points, in...   An Introduction to Partial Differential Equations"This is an introductory book on the subject of partial differential equations which is suitable for a large variety of basic courses on this topic. In particular, it can be used as a textbook or self-study book for large classes of readers with interests in mathematics, engineering, and related fields. Its usefulness stems from its clarity,...   A First Course in Fourier AnalysisThis unique book provides a meaningful resource for applied mathematics through Fourier analysis. It develops a unified theory of discrete and continuous (univariate) Fourier analysis, the fast Fourier transform, and a powerful elementary theory of generalized functions and shows how these mathematical ideas can be used to study sampling theory,...  Differential Equations and Control TheoryThis volume is based on papers presented at the International Workshop on Differential Equations and Optimal Control, held at the Department of Mathematics of Ohio University in Athens, Ohio. The main objective of this international meeting was to feature new trends in the theory and applications of partial differential and functional-differential...   Partial Differential Equations: Modelling and Numerical Simulation (Computational Methods in Applied Sciences)This book is dedicated to Olivier Pironneau. For more than 250 years partial differential equations have been clearly the most important tool available to mankind in order to understand a large variety of phenomena, natural at first and then those originating from human activity and technological development. Mechanics, physics and their...   Introduction to Nonlinear Dispersive Equations (Universitext)The aim of this textbook is to introduce the theory of nonlinear dispersive equations to graduate students in a constructive way. The first three chapters are dedicated to preliminary material, such as Fourier transform, interpolation theory and Sobolev spaces. The authors then proceed to use the linear Schrodinger equation to describe... Result Page: 15 14 13 12 11 10 9 8 7 6