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First Course on Fuzzy Theory and Applications (Advances in Soft Computing)
First Course on Fuzzy Theory and Applications (Advances in Soft Computing)

This basic textbook gives an easily accessible introduction to fuzzy theory and its applications. It provides basic and concrete concepts of the field in a self-contained, condensed and understandable style. This First Course on Fuzzy Theory and Applications includes numerous examples, descriptive illustrations and figures of the basic concepts,...

Handbook of Granular Computing
Handbook of Granular Computing
Although the notion is a relatively recent one, the notions and principles of Granular Computing (GrC) have appeared in a different guise in many related fields including granularity in Artificial Intelligence, interval computing, cluster analysis, quotient space theory and many others. Recent years have witnessed a renewed and expanding interest...
Advanced Data Mining Techniques
Advanced Data Mining Techniques
This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a...
Utility-Based Learning from Data
Utility-Based Learning from Data

Statistical learning — that is, learning from data — and, in particular, probabilistic model learning have become increasingly important in recent years. Advances in information technology have facilitated an explosion of available data. This explosion has been accompanied by theoretical advances, permitting new and...

Reversible Computing
Reversible Computing
The present book is dedicated to Dr. Rolf Landauer, whose early work on the subject of reversible computing inspired me to begin more than 15 years of research in this special corner of computer science. Twice I had the privilege to meet him personally: once inWest Berlin (1992) and once in Boston (1996). Twice he encouraged me...
Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition
Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition

An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms

Key Features

  • Explore statistics and complex mathematics for data-intensive applications
  • Discover new developments in EM algorithm, PCA, and bayesian...
Advances in Minimum Description Length: Theory and Applications (Neural Information Processing)
Advances in Minimum Description Length: Theory and Applications (Neural Information Processing)
The process of inductive inference—to infer general laws and principles from particular instances—is the basis of statistical modeling, pattern recognition, and machine learning. The Minimum Descriptive Length (MDL) principle, a powerful method of inductive inference, holds that the best explanation, given a limited set of observed...
Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras
Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras

Deep learning simplified by taking supervised, unsupervised, and reinforcement learning to the next level using the Python ecosystem

Key Features

  • Build deep learning models with transfer learning principles in Python
  • implement transfer learning to solve real-world research...
Practical Big Data Analytics: Hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R
Practical Big Data Analytics: Hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R

Get command of your organizational Big Data using the power of data science and analytics

Key Features

  • A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions
  • Work with the best tools such as Apache...
Applications of Mathematics in Models, Artificial Neural Networks and Arts: Mathematics and Society
Applications of Mathematics in Models, Artificial Neural Networks and Arts: Mathematics and Society

The book shows a very original organization addressing in a non traditional way, but with a systematic approach, to who has an interest in using mathematics in the social sciences.

The book is divided in four parts: (a) a historical part, written by Vittorio Capecchi which helps us understand the changes in the relationship between...

Neural Networks in Finance : Gaining Predictive Edge in the Market (Advanced Finance Series)
Neural Networks in Finance : Gaining Predictive Edge in the Market (Advanced Finance Series)
"This book clarifies many of the mysteries of Neural Networks and related optimization techniques for researchers in both economics and finance. It contains many practical examples backed up with computer programs for readers to explore. I recommend it to anyone who wants to understand methods used in nonlinear forecasting."
Blake
...
Getting Started With SAS Enterprise Miner 5.2
Getting Started With SAS Enterprise Miner 5.2
SAS defines data mining as the process of uncovering hidden patterns in large amounts of data. Many industries use data mining to address business problems and opportunities such as fraud detection, risk and affinity analyses, database marketing, householding, customer churn, bankruptcy prediction, and...
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