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Fuzzy Set and Its Extension: The Intuitionistic Fuzzy Set
Fuzzy Set and Its Extension: The Intuitionistic Fuzzy Set

Provides detailed mathematical exposition of the fundamentals of fuzzy set theory, including intuitionistic fuzzy sets

This book examines fuzzy and intuitionistic fuzzy mathematics and unifies the latest existing works in literature. It enables readers to fully understand the mathematics of both fuzzy set and...

Decision Science in Action: Theory and Applications of Modern Decision Analytic Optimisation (Asset Analytics)
Decision Science in Action: Theory and Applications of Modern Decision Analytic Optimisation (Asset Analytics)

This book provides essential insights into a range of newly developed numerical optimization techniques with a view to solving real-world problems. Many of these problems can be modeled as nonlinear optimization problems, but due to their complex nature, it is not always possible to solve them using conventional optimization theory....

Python Data Analysis
Python Data Analysis

Key Features

  • Find, manipulate, and analyze your data using the Python 3.5 libraries
  • Perform advanced, high-performance linear algebra and mathematical calculations with clean and efficient Python code
  • An easy-to-follow guide with realistic examples that are frequently used in real-world data...
Problems on Partial Differential Equations (Problem Books in Mathematics)
Problems on Partial Differential Equations (Problem Books in Mathematics)

This book covers a diverse range of topics in Mathematical Physics, linear and nonlinear PDEs. Though the text reflects the classical theory, the main emphasis is on introducing readers to the latest developments based on the notions of weak solutions and Sobolev spaces.

In numerous problems, the student is asked to...

Practical Data Analysis
Practical Data Analysis

Transform, model, and visualize your data through hands-on projects, developed in open source tools

Overview

  • Explore how to analyze your data in various innovative ways and turn them into insight
  • Learn to use the D3.js visualization tool for exploratory data analysis
  • ...
OpenCV 3 Computer Vision with Python Cookbook: Leverage the power of OpenCV 3 and Python to build computer vision applications
OpenCV 3 Computer Vision with Python Cookbook: Leverage the power of OpenCV 3 and Python to build computer vision applications

Recipe-based approach to tackle the most common problems in Computer Vision by leveraging the functionality of OpenCV using Python APIs

Key Features

  • Build computer vision applications with OpenCV functionality via Python API
  • Get to grips with image processing, multiple...
Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)
Bayesian Data Analysis, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)
This book is intended to have three roles and to serve three associated audiences: an introductory text on Bayesian inference star ting from first principles, a graduate text on effective current approaches to Bayesian modeling and computation in statistics and related fields, and a handbook of Bayesian meth ods in applied...
Data Science Fundamentals for Python and MongoDB
Data Science Fundamentals for Python and MongoDB
Build the foundational data science skills necessary to work with and better understand complex data science algorithms. This example-driven book provides complete Python coding examples to complement and clarify data science concepts, and enrich the learning experience. Coding examples include visualizations whenever appropriate....
Digital Signal Processing with Examples in MATLAB® (Electrical Engineering & Applied Signal Processing Series)
Digital Signal Processing with Examples in MATLAB® (Electrical Engineering & Applied Signal Processing Series)

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...

Approximation Methods for Polynomial Optimization: Models, Algorithms, and Applications (SpringerBriefs in Optimization)
Approximation Methods for Polynomial Optimization: Models, Algorithms, and Applications (SpringerBriefs in Optimization)
Polynomial optimization, as its name suggests, is used to optimize a generic multivariate polynomial function, subject to some suitable polynomial equality and/or inequality constraints. Such problem formulation dates back to the nineteenth century when the relationship between nonnegative polynomials and sum of squares (SOS) was...
Neural Network Programming with TensorFlow: Unleash the power of TensorFlow to train efficient neural networks
Neural Network Programming with TensorFlow: Unleash the power of TensorFlow to train efficient neural networks

Neural Networks and their implementation decoded with TensorFlow

About This Book

  • Develop a strong background in neural network programming from scratch, using the popular Tensorflow library.
  • Use Tensorflow to implement different kinds of neural networks – from simple...
Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R
Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R
Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in Excel so...
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