12 Applications

12.1 Large Scale Deep Learning

12.1.1 Fast CPU Implementations

12.1.2 GPU Implementations

12.1.3 Large Scale Distributed Implementations

12.1.4 Model Compression

12.1.5 Dynamic Structure

12.1.6 Specialized Hardware Implementations of Deep Networks

12.2 Computer Vision

12.2.1 Preprocessing Contrast Normalization Dataset Augmentation

12.3 Speech Recognition

12.4 Natural Language Processing

12.4.1 $n$-grams

12.4.2 Neural Language Models

12.4.3 High-Dimensional Outputs Use of a Short List Hierarchical Softmax Importance Sampling Noise-Contrastive Estimation and Ranking Loss

12.4.4 Combining Neural Language Models with $n$-grams

12.4.5 Neural Machine Translation Using an attention Mechanism and Aligning Pieces of Data

12.4.6 Historical Perspective

12.5 Other Applications

12.5.1 Recommender Systems Exploration versus Exploitation

12.5.2 Knowledge Representation, Reasoning and Question Answering Knowledge, Relations and Question Answering