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Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries

Key Features

  • Build a strong foundation in neural networks and deep learning with Python libraries
  • Explore advanced deep learning techniques and their applications...
Selected Works of A.N. Kolmogorov: Volume III: Information Theory and the Theory of Algorithms
Selected Works of A.N. Kolmogorov: Volume III: Information Theory and the Theory of Algorithms

This volume is the last of three volumes devoted to the work of one of the most prominent 20th century mathematicians. Throughout his mathematical work, A.N. Kolmogorov (1903-1987) showed great creativity and versatility and his wide-ranging studies in many different areas, led to the solution of conceptual and fundamental problems and the...

Numerical Methods in Finance and Economics: A MATLAB-Based Introduction (Statistics in Practice)
Numerical Methods in Finance and Economics: A MATLAB-Based Introduction (Statistics in Practice)

A state-of-the-art introduction to the powerful mathematical and statistical tools used in the field of finance The use of mathematical models and numerical techniques is a practice employed by a growing number of applied mathematicians working on applications in finance. Reflecting this development, Numerical Methods in Finance and...

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...

R for SAS and SPSS Users (Statistics and Computing)
R for SAS and SPSS Users (Statistics and Computing)

While SAS and SPSS have many things in common, R is very different. My goal in writing this book is to help you translate what you know about SAS or SPSS into a working knowledge of R as quickly and easily as possible. I point out how they differ using terminology with which you are familiar, and show you which add-on packages will...

Data Mashups in R
Data Mashups in R

Programmers may spend a good part of their careers scripting code to conform to commercial statistics packages, visualization tools, and domain-specific third-party software. The same tasks can force end users to spend countless hours in copy-paste purgatory, each minor change necessitating another grueling round of formatting tabs and...

Advances in Knowledge Discovery and Data Mining: 15th Pacific-Asia Conference, PAKDD 2011
Advances in Knowledge Discovery and Data Mining: 15th Pacific-Asia Conference, PAKDD 2011

PAKDD has been recognized as a major international conference in the areas of data mining (DM) and knowledge discovery in databases (KDD). It provides an international forum for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all KDD-related areas...

Energy Minimization Methods in Computer Vision and Pattern Recognition: 8th International Conference, EMMCVPR 2011
Energy Minimization Methods in Computer Vision and Pattern Recognition: 8th International Conference, EMMCVPR 2011

Over the last few decades, energy minimization methods have become an established paradigm to resolve a variety of challenges in the fields of computer vision and pattern recognition. While traditional approaches to computer vision were often based on a heuristic sequence of processing steps and merely allowed a very limited...

Neural Networks and Computing: Learning Algorithms and Applications
Neural Networks and Computing: Learning Algorithms and Applications

The area of Neural computing that we shall discuss in this book represents a combination of techniques of classical optimization, statistics, and information theory. Neural network was once widely called artificial neural networks, which represented how the emerging technology was related to artificial intelligence. It once was a topic that...

Fundamentals of Predictive Text Mining (Texts in Computer Science)
Fundamentals of Predictive Text Mining (Texts in Computer Science)

Five years ago, we authored “Text Mining: Predictive Methods for Analyzing Unstructured Information.” That book was geared mostly to professional practitioners, but was adaptable to course work with some effort by the instructor. Many topics were evolving, and this was one of the earliest efforts to collect material for predictive...

Bioinformatics: The Machine Learning Approach, Second Edition (Adaptive Computation and Machine Learning)
Bioinformatics: The Machine Learning Approach, Second Edition (Adaptive Computation and Machine Learning)

We have been very pleased, beyond our expectations, with the reception of the first edition of this book. Bioinformatics, however, continues to evolve very rapidly, hence the need for a new edition. In the past three years, fullgenome sequencing has blossomed with the completion of the sequence of the fly and the first draft of the...

Data Mining: A Heuristic Approach
Data Mining: A Heuristic Approach

The last decade has witnessed a revolution in interdisciplinary research where the boundaries of different areas have overlapped or even disappeared. New fields of research emerge each day where two or more fields have integrated to form a new identity. Examples of these emerging areas include bioinformatics (synthesizing biology with...

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