Book Content
chapters • 19h16m total length
1. Getting Started with Next-Generation Artificial Intelligence through Reinforcement Learning
2. Building a Reward Matrix – Designing Your Datasets
3. Machine Intelligence – Evaluation Functions and Numerical Convergence
4. Optimizing Your Solutions with K-Means Clustering
5. How to Use Decision Trees to Enhance K-Means Clustering
6. Innovating AI with Google Translate
7. Optimizing Blockchains with Naive Bayes
8. Solving the XOR Problem with a Feedforward Neural Network
9. Abstract Image Classification with Convolutional Neural Networks (CNN)
10. Conceptual Representation Learning
11. Combining Reinforcement Learning and Deep Learning
12. AI and the Internet of Things (IoT)
13. Visualizing Networks with TensorFlow 2.x and TensorBoard
14. Preparing the Input of Chatbots with Restricted Boltzmann Machines (RBMs) and Principal Component Analysis (PCA)
15. Setting Up a Cognitive NLP UI/CUI Chatbot
16. Improving the Emotional Intelligence Deficiencies of Chatbots
17. Genetic Algorithms in Hybrid Neural Networks
18. Neuromorphic Computing
19. Quantum Computing
20. Appendix - Answers to the Questions
