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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...
Reactive Systems: Modelling, Specification and Verification
Reactive Systems: Modelling, Specification and Verification
Formal methods is the term used to describe the specification and verification of software and software systems using mathematical logic. Various methodologies have been developed and incorporated into software tools. An important subclass is distributed systems. There are many books that look at particular methodologies for such systems, e.g. CSP,...
Software Evolution
Software Evolution
Software has become omnipresent and vital in our information-based society, so all software producers should assume responsibility for its reliability. While "reliable" originally assumed implementations that were effective and mainly error-free, additional issues like adaptability and maintainability have gained equal importance...
Introduction to Parallel Processing: Algorithms and Architectures (Series in Computer Science)
Introduction to Parallel Processing: Algorithms and Architectures (Series in Computer Science)
The field of digital computer architecture has grown explosively in the past two decades. Through a steady stream of experimental research, tool-building efforts, and theoretical studies, the design of an instruction-set architecture, once considered an art, has been transformed into one of the most quantitative branches of...
Scientific Computing with Python 3
Scientific Computing with Python 3

Key Features

  • Your ultimate resource for getting up and running with Python numerical computations
  • Explore numerical computing and mathematical libraries using Python 3.x code with SciPy and NumPy modules
  • A hands-on guide to implementing mathematics with Python, with complete...
Intelligent Mobile Projects with TensorFlow: Build 10+ Artificial Intelligence apps using TensorFlow Mobile and Lite for iOS, Android, and Raspberry Pi
Intelligent Mobile Projects with TensorFlow: Build 10+ Artificial Intelligence apps using TensorFlow Mobile and Lite for iOS, Android, and Raspberry Pi

Create Deep Learning and Reinforcement Learning apps for multiple platforms with TensorFlow

Key Features

  • Build TensorFlow-powered AI applications for mobile and embedded devices
  • Learn modern AI topics such as computer vision, NLP, and deep reinforcement learning
  • ...
Java How to Program, 7th Edition
Java How to Program, 7th Edition

The Deitels' groundbreaking How to Program series offers unparalleled breadth and depth of object-oriented programming concepts and intermediate-level topics for further study. The Seventh Edition has been extensively fine-tuned and is completely up-to-date with Sun Microsystems, Inc.’s...

The Handbook of Brain Theory and Neural Networks: Second Edition
The Handbook of Brain Theory and Neural Networks: Second Edition
Dramatically updating and extending the first edition, published in 1995, the second edition of The Handbook of Brain Theory and Neural Networks presents the enormous progress made in recent years in the many subfields related to the two great questions: How does the brain work? and, How can we build intelligent machines?

Once
...
Parallel Complexity Theory (Research Notes in Theoretical Computers Science)
Parallel Complexity Theory (Research Notes in Theoretical Computers Science)

Parallel complexity theory, the study of resource-bounded parallel computation, is surely one of the fastest-growing areas of theoretical Computer Science. In the light of this, it would be foolish to attempt an encyclopedic coverage of the field. However, it is the belief of the author that its foundations are becoming increas ingly...

Subband Adaptive Filtering: Theory and Implementation
Subband Adaptive Filtering: Theory and Implementation

Subband adaptive filtering is rapidly becoming one of the most effective techniques for reducing computational complexity and improving the convergence rate of algorithms in adaptive signal processing applications. This book provides an introductory, yet extensive guide on the theory of various subband adaptive filtering techniques. For...

Fast Data Processing with Spark (Community Experience Distilled)
Fast Data Processing with Spark (Community Experience Distilled)

High-speed distributed computing made easy with Spark

Overview

  • Implement Spark's interactive shell to prototype distributed applications
  • Deploy Spark jobs to various clusters such as Mesos, EC2, Chef, YARN, EMR, and so on
  • Use Shark's SQL query-like syntax with...
Image Processing: Tensor Transform and Discrete Tomography with MATLAB ®
Image Processing: Tensor Transform and Discrete Tomography with MATLAB ®

Focusing on mathematical methods in computer tomography, Image Processing: Tensor Transform and Discrete Tomography with MATLAB® introduces novel approaches to help in solving the problem of image reconstruction on the Cartesian lattice. Specifically, it discusses methods of image processing along...

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