Parallel Computing For Data Science

Author: Norman Matloff
Publisher: CRC Press
ISBN: 1466587032
Size: 46.23 MB
Format: PDF
View: 1300
Parallel Computing for Data Science: With Examples in R, C++ and CUDA is one of the first parallel computing books to concentrate exclusively on parallel data structures, algorithms, software tools, and applications in data science. It includes examples not only from the classic "n observations, p variables" matrix format but also from time series, network graph models, and numerous other structures common in data science. The examples illustrate the range of issues encountered in parallel programming. With the main focus on computation, the book shows how to compute on three types of platforms: multicore systems, clusters, and graphics processing units (GPUs). It also discusses software packages that span more than one type of hardware and can be used from more than one type of programming language. Readers will find that the foundation established in this book will generalize well to other languages, such as Python and Julia.

Quantitative Trading

Author: Xin Guo
Publisher: CRC Press
ISBN: 1498706495
Size: 53.25 MB
Format: PDF, Mobi
View: 6653
The first part of this book discusses institutions and mechanisms of algorithmic trading, market microstructure, high-frequency data and stylized facts, time and event aggregation, order book dynamics, trading strategies and algorithms, transaction costs, market impact and execution strategies, risk analysis, and management. The second part covers market impact models, network models, multi-asset trading, machine learning techniques, and nonlinear filtering. The third part discusses electronic market making, liquidity, systemic risk, recent developments and debates on the subject.

Author: Γιώργος Σιμόπουλος
ISBN: 9789601628158
Size: 49.18 MB
Format: PDF, Mobi
View: 1093