TY  - BOOK
AU  - Beysolow,Taweh,II
TI  - Introduction to deep learning using R : a step-by-step guide to learning and implementing deep learning models using R
T2  - For professionals by professionals
SN  - 9781484227336
U1  - 006.31 
PY  - 2017///
CY  - New York?
PB  - Apress
KW  - Machine learning
KW  - Big data
KW  - R (Computer program language)
N1  - Includes index; Introduction to deep learning -- Mathematical review -- A review of optimization and machine learning -- Single and multilayer perceptron models -- Convolutional neural networks (CNNs) -- Recurrent neural networks (RNNs) -- Autoencoders, restricted boltzmann machines, and deep belief networks -- Experimental design and heuristics -- Hardware and software suggestions -- Machine learning example problems -- Deep learning and other example problems -- Closing statements
N2  - Understand deep learning, the nuances of its different models, and where these models can be applied. The abundance of data and demand for superior products/services have driven the development of advanced computer science techniques, among them image and speech recognition. Introduction to Deep Learning Using R provides a theoretical and practical understanding of the models that perform these tasks by building upon the fundamentals of data science through machine learning and deep learning. This step-by-step guide will help you understand the disciplines so that you can apply the methodology in a variety of contexts. All examples are taught in the R statistical language, allowing students and professionals to implement these techniques using open source tools. What You Will Learn: • Understand the intuition and mathematics that power deep learning models • Utilize various algorithms using the R programming language and its packages • Use best practices for experimental design and variable selection • Practice the methodology to approach and effectively solve problems as a data scientist • Evaluate the effectiveness of algorithmic solutions and enhance their predictive power
ER  -