Big-Data Analytics for Cloud, IoT and Cognitive Computing

8Deep Reinforcement Learning and Social Media Analytics

CHAPTER OUTLINE

1. 8.1 Deep Learning Systems and Social Media Industry
   1. 8.1.1 Deep Learning Systems and Software Support
   2. 8.1.2 Reinforcement Learning Principles
   3. 8.1.3 Social-Media Industry and Global Impact
2. 8.2 Text and Image Recognition using ANN and CNN
   1. 8.2.1 Numeral Recognition using TensorFlow for ANN
   2. 8.2.2 Numeral Recognition using Convolutional Neural Networks
   3. 8.2.3 Convolutional Neural Networks for Face Recognition
   4. 8.2.4 Medical Text Analytics by Convolutional Neural Networks
3. 8.3 DeepMind with Deep Reinforcement Learning
   1. 8.3.1 Google DeepMind AI Programs
   2. 8.3.2 Deep Reinforcement Learning Algorithm
   3. 8.3.3 Google AlphaGo Game Competition
   4. 8.3.4 Flappybird Game using Reinforcement Learning
4. 8.4 Data Analytics for Social-Media Applications
   1. 8.4.1 Big Data Requirements in Social-Media Applications
   2. 8.4.2 Social Networks and Graph Analytics
   3. 8.4.3 Predictive Analytics Software Tools
   4. 8.4.4 Community Detection in Social Networks
5. 8.5 Conclusions

8.1 Deep Learning Systems and Social Media Industry

In this chapter, we introduce the software libraries or platforms that have been developed by industry and academia for machine learning (ML) and deep learning (DL) applications. As studied in earlier chapters, deep learning is part of a broader family of machine learning methods. The difference lies in the learning representations of data. For example, the inspection of an X-ray image is represented in many ways such ...