Both a radical feminist history and a street art resource, this handbook combines short biographies with striking and usable stencil images of 30 female activists, anarchists, feminists, freedom fighters, and visionaries. From Harriet Tubman, Emma Goldman, and Angela Davis to Vandana Shiva, Sylvia...
Solve machine learning problems using probabilistic graphical models implemented in Python with real-world applications
About This Book
Stretch the limits of machine learning by learning how graphical models provide an insight on particular problems, especially in high dimension areas such as image...
Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book...
This thesis is concerned with the design of efficient algorithms for listing combinatorial structures. The research described here gives some answers to the following questions: which families of combinatorial structures have fast computer algorithms for listing their members, What general methods are useful for listing combinatorial...
This thesis is concerned with the design of efficient algorithms for listing combinatorial structures. The research described here gives some answers to the following questions: which families of combinatorial structures have fast computer algorithms for listing their members, What general methods are useful for listing combinatorial...
This book is Volume III of the series DSP for MATLAB™ and LabVIEW™. Volume III covers digital filter design, including the specific topics of FIR design via windowed-ideal-lowpass filter, FIR highpass, bandpass, and bandstop filter design from windowed-ideal lowpass filters, FIR design using the transition-band-optimized Frequency...
Most books on data mining focus on principles and furnish few instructions on how to carry out a data mining project. Data Mining Using SAS Applications not only introduces the key concepts but also enables readers to understand and successfully apply data mining methods using powerful yet user-friendly SAS macro-call files. These methods...
Based on fundamental principles from mathematics, linear systems, and signal analysis, digital signal processing (DSP) algorithms are useful for extracting information from signals collected all around us. Combined with today’s powerful computing capabilities, they can be used in a wide range of application areas, including...
Full of biological applications, exercises, and interactive graphical examples, Foundational and Applied Statistics for Biologists Using R presents comprehensive coverage of both modern analytical methods and statistical foundations. The author harnesses the inherent properties of the R environment to enable students...
This book gives a comprehensive and systematic review of secure compressive sensing (CS) for applications in various fields such as image processing, pattern recognition, Internet of things (IoT), and cloud computing. It will help readers grasp the knowledge of secure CS and its applications, and stimulate more readers to work on the research...
This book tackles all the stages and mechanisms involved in the learning of manipulation tasks by bimanual robots in unstructured settings, as it can be the task of folding clothes.
The first part describes how to build an integrated system, capable of properly handling the kinematics and dynamics of the robot along the...
