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Machine Learning Paradigms: Advances in Data Analytics (Intelligent Systems Reference Library, 149)
Machine Learning Paradigms: Advances in Data Analytics (Intelligent Systems Reference Library, 149)

This book explores some of the emerging scientific and technological areas in which the need for data analytics arises and is likely to play a significant role in the years to come. At the dawn of the 4th Industrial Revolution, data analytics is emerging as a force that drives towards dramatic changes in our daily lives, the...

Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data
Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data

Due to advances in sensor, storage, and networking technologies, data is being generated on a daily basis at an ever-increasing pace in a wide range of applications, including cloud computing, mobile Internet, and medical imaging. This large multidimensional data requires more efficient dimensionality reduction schemes than the traditional...

Serverless Web Applications with React and Firebase: Develop real-time applications for web and mobile platforms
Serverless Web Applications with React and Firebase: Develop real-time applications for web and mobile platforms

Build rich and collaborative applications using client-side code with React, Redux, and Firebase

Key Features

  • A practical guide covering the full stack for web development with React 16 and Firebase
  • Leverage the power of Firebase Cloud Storage, messaging, functions, OAuth,...
Graph Algorithms
Graph Algorithms
Shimon was a great computer scientist who inspired generations of Israeli stutents and young researchers, including many future leaders of theoretical computer science.

He was a master at creating combinatorial algorithms, constructions, and proofs. He always sought the simplest and most lucid solutions. Because
...
Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks
Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks

Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You’ll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and...

Matrix Information Geometry
Matrix Information Geometry

This book presents advances in matrix and tensor data processing in the domain of signal, image and information processing. The theoretical mathematical approaches are discusses in the context of potential applications in sensor and cognitive systems engineering.
The topics and application include Information Geometry, Differential
...

Applied Calculus of Variations for Engineers
Applied Calculus of Variations for Engineers

The subject of calculus of variations is to find optimal solutions to engineering problems where the optimum may be a certain quantity, a shape, or a function. Applied Calculus of Variations for Engineers addresses this very important mathematical area applicable to many engineering disciplines. Its unique,...

Python Machine Learning
Python Machine Learning

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics

About This Book

  • Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization
  • Learn effective strategies and best practices to...
Digital Dice: Computational Solutions to Practical Probability Problems
Digital Dice: Computational Solutions to Practical Probability Problems

"Paul Nahin's Digital Dice is a marvelous book, one that is even better than his Duelling Idiots. Nahin presents twenty-one great probability problems, from George Gamow's famous elevator paradox (as corrected by Donald Knuth) to a bewildering puzzle involving two rolls of toilet paper, and he solves them all with the aid...

Machine Learning Using R: With Time Series and Industry-Based Use Cases in R
Machine Learning Using R: With Time Series and Industry-Based Use Cases in R

Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use it to build a ML model from raw data. You will see how to use R programming with TensorFlow, thus avoiding the effort of learning Python...

Linear Fresnel Reflector Systems for Solar Radiation Concentration: Theoretical Analysis, Mathematical Formulation and Parameters’ Computation using MATLAB
Linear Fresnel Reflector Systems for Solar Radiation Concentration: Theoretical Analysis, Mathematical Formulation and Parameters’ Computation using MATLAB
This book offers a complete guide to designing Linear Fresnel Reflector Systems for concentrating solar radiation. It includes theoretical analyses, computational tools and mathematical formulae to facilitate the development, design, construction and application of these systems. In addition, the book presents a concise yet thorough...
Differential Geometry: Bundles, Connections, Metrics and Curvature (Oxford Graduate Texts in Mathematics, Vol. 23)
Differential Geometry: Bundles, Connections, Metrics and Curvature (Oxford Graduate Texts in Mathematics, Vol. 23)

Bundles, connections, metrics and curvature are the 'lingua franca' of modern differential geometry and theoretical physics. This book will supply a graduate student in mathematics or theoretical physics with the fundamentals of these objects.

Many of the tools used in differential topology are introduced and the
...

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