Introduction to Deep Learning Using R

1. Introduction to Deep Learning
Taweh Beysolow II

2. Mathematical Review
Taweh Beysolow II

3. A Review of Optimization and Machine Learning
Taweh Beysolow II

4. Single and Multilayer Perceptron Models
Taweh Beysolow II

5. Convolutional Neural Networks (CNNs)
Taweh Beysolow II

6. Recurrent Neural Networks (RNNs)
Taweh Beysolow II

7. Autoencoders, Restricted Boltzmann Machines, and Deep Belief Networks
Taweh Beysolow II

8. Experimental Design and Heuristics
Taweh Beysolow II

9. Hardware and Software Suggestions
Taweh Beysolow II

10. Machine Learning Example Problems
Taweh Beysolow II

11. Deep Learning and Other Example Problems
Taweh Beysolow II

12. Closing Statements
Taweh Beysolow II

Avainsanat: Business and Management, Big Data/Analytics, Computing Methodologies, Programming Languages, Compilers, Interpreters