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Applied Statistics: Theory and Problem Solutions with R
Applied Statistics: Theory and Problem Solutions with R

Instructs readers on how to use methods of statistics and experimental design with R software 

Applied statistics covers both the theory and the application of modern statistical and mathematical modelling techniques to applied problems in industry, public services, commerce, and research. It proceeds...

Graphical Models with R (Use R!)
Graphical Models with R (Use R!)
Graphical models in their modern form have been around since the late 1970s and appear today in many areas of the sciences. Along with the ongoing developments of graphical models, a number of different graphical modelling software programs have been written over the years. In recent years many of these software developments have...
Modelling Metabolism with Mathematica
Modelling Metabolism with Mathematica
With the advent of sophisticated general programming environments like Mathematica, the task of developing new models of metabolism and visualizing their responses has become accessible to students of biochemistry and the life sciences in general. Modelling Metabolism with Mathematica presents the approaches, methods, tools, and algorithms...
Natural Language Processing with TensorFlow: Teach language to machines using Python's deep learning library
Natural Language Processing with TensorFlow: Teach language to machines using Python's deep learning library

Write modern natural language processing applications using deep learning algorithms and TensorFlow

Key Features

  • Focuses on more efficient natural language processing using TensorFlow
  • Covers NLP as a field in its own right to improve understanding for choosing TensorFlow...
Python Deep Learning Projects: 9 projects demystifying neural network and deep learning models for building intelligent systems
Python Deep Learning Projects: 9 projects demystifying neural network and deep learning models for building intelligent systems

Insightful projects to master deep learning and neural network architectures using Python and Keras

Key Features

  • Explore deep learning across computer vision, natural language processing (NLP), and image processing
  • Discover best practices for the training of deep neural...
Learning Predictive Analytics with Python: Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python
Learning Predictive Analytics with Python: Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python

Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python

About This Book

  • A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices
  • Get to grips with the basics of Predictive...
Stochastic Approximation and Recursive Algorithms and Applications (Stochastic Modelling and Applied Probability) (v. 35)
Stochastic Approximation and Recursive Algorithms and Applications (Stochastic Modelling and Applied Probability) (v. 35)

This book presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both constrained and unconstrained problems. This second edition is a thorough revision, although the main features and structure remain unchanged. It contains many additional applications and results as...

Case Studies in Bayesian Statistical Modelling and Analysis
Case Studies in Bayesian Statistical Modelling and Analysis

Provides an accessible foundation to Bayesian analysis using real world models

This book aims to present an introduction to Bayesian modelling and computation, by considering real case studies drawn from diverse fields spanning ecology, health, genetics and finance. Each chapter comprises a description of the problem, the...

Fuzzy Systems Engineering: Theory and Practice (Studies in Fuzziness and Soft Computing)
Fuzzy Systems Engineering: Theory and Practice (Studies in Fuzziness and Soft Computing)

This book is devoted to reporting innovative and significant progress in fuzzy system engineering. Given the maturation of fuzzy logic, this book is dedicated to exploring the recent breakthroughs in fuzziness and soft computing in favour of intelligent system engineering. This monograph presents novel developments of the fuzzy theory as well as...

Intelligent Control: A Hybrid Approach Based on Fuzzy Logic, Neural Networks and Genetic Algorithms (Studies in Computational Intelligence)
Intelligent Control: A Hybrid Approach Based on Fuzzy Logic, Neural Networks and Genetic Algorithms (Studies in Computational Intelligence)

Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type...

Ultra-Wideband Wireless Communications and Networks
Ultra-Wideband Wireless Communications and Networks
Ultra-wideband (UWB) technology has great potential for applications in wireless communications, radar and location. It has many benefits due to its ultra-wideband nature, which include high data rate, less path loss and better immunity to multipath propagation, availability of low-cost transceivers, low transmit power and low interference. Despite...
Deep Learning: Practical Neural Networks with Java
Deep Learning: Practical Neural Networks with Java

Build and run intelligent applications by leveraging key Java machine learning libraries

About This Book

  • Develop a sound strategy to solve predictive modelling problems using the most popular machine learning Java libraries.
  • Explore a broad variety of data processing, machine learning,...
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