The singular value decomposition (SVD) is not only a classical theory in matrix computation and analysis, but also is a powerful tool in ma- chine learning and modern data analysis. In this tutorial we first study the basic notion of SVD and then sh
graph processing， 高性能计算。 Breadth-First Search (BFS) is a core primitive for graph traversal and a basis for many higher-level graph analysis algorithms. It is also representative of a class of parallel computations whose memory accesses and work dis
At the end of the day, there is nothing that can be done in Mathematica and absolutely can not be done in other programming environments. For many problems however, especially those involving symbolic programming, solving a problem in a language suc
This text is written for a. high school graduates preparing to take business or science courses at community colleges or universities b. working professionals who feel that they need a math review from the very beginning c. young students and workin
NumPy is an extension of Python, which provides highly optimized arrays and numerical operations. NumPy replaces a lot of the functionality of Matlab and Mathematica specifically vectorized operations, but in contrast to those products is free and o
Scientific computing is the study of how to use computers effectively to solve problems that arise from the mathematical modeling of phenomena in science and engineering. It is based on mathematics, numerical and symbolic/algebraic computations and
Machine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Pub
Machine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Pub
Key FeaturesLearn about the statistics behind powerful predictive models with p-value, ANOVA, and F- statistics.Implement statistical computations programmatically for supervised and unsupervised learning through K-means clustering.Master the statis
Abstract-The use of the fast Fourier transform in power spectrum analysis is described. Principal advantages of this method area reduction in the number of computations and in required core storage, and convenient application in nonstationarity test
目录 Table of Contents. 1 Preface 1 Introduction. 1 1.1 What is image processing pipeline?. 1 1.2 What does web image processing pipeline consist of?. 3 1.3 What are big data microscopy experiments?. 4 1.4 Why are scientists interested in big data mic
Explore machine learning concepts using the latest numerical computing library — TensorFlow — with the help of this comprehensive cookbook About This Book Your quick guide to implementing TensorFlow in your day-to-day machine learning activities Lea
Bayesian statistics has been around for more than 250 years now. During this time it has enjoyed as much recognition and appreciation as disdain and contempt. Through the last few decades it has gained more and more attention from people in statisti
用于计算溶剂的密度、粘度等性质。Sednterp stores the basic physical data and the fitted coefficients for interpretations in the phyconst database file. Storing all of this information in a single file helps in the program set up and in the updating of the algorithms
Introducation to Parallel Computing is a complete end-to-end source of information on almost all aspects of parallel computing from introduction to architectures to programming paradigms to algorithms to programming standards. It is the only book to
Tensorflow is the most popular Deep Learning Library out there. It has fantastic graph computations feature which helps data scientist to visualize his designed neural network using TensorBoard. This Machine learning library supports both Convolutio
