Business & Economics Books:

Deep Belief Nets in C++ and CUDA C: Volume 3

Convolutional Nets



Customer rating

Click to share your rating 0 ratings (0.0/5.0 average) Thanks for your vote!

Share this product

Deep Belief Nets in C++ and CUDA C: Volume 3 by Timothy Masters

Pre-order to reserve stock from our first shipment. Your credit card will not be charged until your order is ready to ship.

Available for pre-order now
Pre-order Price Guarantee

If you pre-order an item and the price drops before the release date, you’ll pay the lowest price. This happens automatically when you pre-order and pay by credit card or pickup.

If paying by PayPal or internet banking, and the price drops after you have paid, you can ask for the difference to be refunded. Find out more

If Mighty Ape's price changes before release, you'll pay the lowest price.


This product will be released on

Delivering to:

It should arrive:

  • 6 September using standard courier delivery


Discover the essential building blocks of a common and powerful form of deep belief network: convolutional nets. This book shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a `thought process' that is capable of learning abstract concepts built from simpler primitives. These models are especially useful for image processing applications. At each step Deep Belief Nets in C++ and CUDA C: Volume 3 presents intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with CUDA-capable video display cards. Source code for all routines presented in the book, and the executable CONVNET program which implements these algorithms, are available for free download. What You Will Learn Discover convolutional nets and how to use them Build deep feedforward nets using locally connected layers, pooling layers, and softmax outputs Master the various programming algorithms required Carry out multi-threaded gradient computations and memory allocations for this threading Work with CUDA code implementations of all core computations, including layer activations and gradient calculations Make use of the CONVNET program and manual to explore convolutional nets and case studies Who This Book Is For Those who have at least a basic knowledge of neural networks and some prior programming experience, although some C++ and CUDA C is recommended.

Author Biography

Timothy Masters received a PhD in mathematical statistics with a specialization in numerical computing. Since then he has continuously worked as an independent consultant for government and industry. His early research involved automated feature detection in high-altitude photographs while he developed applications for flood and drought prediction, detection of hidden missile silos, and identification of threatening military vehicles. Later he worked with medical researchers in the development of computer algorithms for distinguishing between benign and malignant cells in needle biopsies. For the last twenty years he has focused primarily on methods for evaluating automated financial market trading systems. He has authored five books on practical applications of predictive modeling: Practical Neural Network Recipes in C++ (Academic Press, 1993); Signal and Image Processing with Neural Networks (Wiley, 1994); Advanced Algorithms for Neural Networks (Wiley, 1995); Neural, Novel, and Hybrid Algorithms for Time Series Prediction (Wiley, 1995); Data Mining Algorithms in C++ (Apress, 2018); Assessing and Improving Prediction and Classification (Apress, 2018); Deep Belief Nets in C++ and CUDA C: Volume 1 (Apress, 2018); and Deep Belief Nets in C++ and CUDA C: Volume 2 (Apress, 2018).
Release date NZ
September 5th, 2018
Country of Publication
United States
1st ed.
12 Illustrations, black and white; IV, 109 p. 12 illus.
Product ID

Customer previews

Nobody has previewed this product yet. You could be the first!

Write a Preview

Help & options

  • If you think we've made a mistake or omitted details, please send us your feedback. Send Feedback
  • If you have a question or problem with this product, visit our Help section. Get Help
  • Seen a lower price for this product elsewhere? We'll do our best to beat it. Request a better price
Filed under...

Buy this and earn 290 Banana Points