Deep Learning Cookbook

Deep Learning Cookbook

Deep learning doesn’t have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, you’ll learn how to solve…

Deep Learning with R

Deep Learning with R

Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples.

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

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

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…

Robot Operating System for Absolute Beginners

Robot Operating System for Absolute Beginners

Learn how to get started with robotics programming using Robot Operation System (ROS). Targeted for absolute beginners in ROS, Linux, and Python, this short guide shows you how to build your own robotics projects. ROS is an open-source and flexible framework for writing robotics software. With a hands-on…

Deep Belief Nets in C++ and CUDA C: Volume 1

Deep Belief Nets in C++ and CUDA C: Volume 1

Discover the essential building blocks of the most common forms of deep belief networks. At each step this book provides 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…

Assessing and Improving Prediction and Classification

Assessing and Improving Prediction and Classification

Assess the quality of your prediction and classification models in ways that accurately reflect their real-world performance, and then improve this performance using state-of-the-art algorithms such as committee-based decision making, resampling the dataset, and boosting.  This book presents many important techniques for building powerful, robust models and quantifying…