Learn IT - Books tags neural

Nostradamus 2013: Prediction, Modeling and Analysis of Complex Systems (Advances in Intelligent Systems and Computing)

Springer, 2013

Prediction of behavior of the dynamical systems, analysis and modeling of its structure is vitally important problem in engineering, economy and science today.

Examples of such systems can be seen in the world around us and of course in almost every scientific discipline including such “exotic” domains like the...

Design of Logic-based Intelligent Systems

John Wiley & Sons, 2004

Principles for constructing intelligent systems
Design of Logic-based Intelligent Systems develops principles andmethods for constructing intelligent systems for complex tasks thatare readily done by humans but are difficult for machines. CurrentArtificial Intelligence (AI) approaches rely on various constructsand methods (production...

Applied Text Analysis with Python: Enabling Language-Aware Data Products with Machine Learning

O'Reilly, 2018

From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural...

Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning

O'Reilly, 2018

This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or...

Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models

John Wiley & Sons, 2009

This book was written in response to the growing demand for a text that provides a unified treatment of linear and nonlinear complex valued adaptive filters, and methods for the processing of general complex signals (circular and noncircular). It brings together adaptive filtering algorithms for feedforward (transversal) and feedback...

Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs)

Cambridge University Press, 2016

The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. “Big data,” “data science,” and “machine learning” have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science...

Java for Data Science

Packt Publishing, 2017

Examine the techniques and Java tools supporting the growing field of data science About This Book Your entry ticket to the world of data science with the stability and power of Java Explore, analyse, and visualize your data effectively using easy-to-follow examples Make your Java applications more capable using machine learning Who This Book Is...

Artificial Intelligence: First CCF International Conference, ICAI 2018, Jinan, China, August 9-10, 2018, Proceedings (Communications in Computer and Information Science)

Springer, 2018

This book constitutes the refereed proceedings of the First CCF International Conference on Artificial Intelligence, CCF-ICAI 2018, held in Jinan, China in August, 2018. The 17 papers presented were carefully reviewed and selected from 82 submissions. The papers are organized in topical sections on unsupervised...

Classification and Learning Using Genetic Algorithms: Applications in Bioinformatics and Web Intelligence (Natural Computing Series)

Springer, 2007

Genetic algorithms (GAs) are randomized search and optimization techniques guided by the principles of evolution and natural genetics; they have a large amount of implicit parallelism. GAs perform multimodal search in complex landscapes and provide near-optimal solutions for objective or tness func tion of an...

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

Springer, 2019

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource...

Data Mining and Statistics for Decision Making

John Wiley & Sons, 2011

Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify...

Computer Science: Notable Research and Discoveries (Frontiers of Science)

Facts on File, 2010

No one is certain how much more powerful and possibly intelligent computers will become in the 21st century. Exploring six prominent topics in computer science research, this title describes how computer scientists conduct research and attempt to formulate answers to important questions. Research published in journals, presented at conferences,...

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