Introduction to Intricate Artificial Psychology with Python unlocks the mysteries of Intricate Artificial Psychology (iAp). This comprehensive guide takes readers through advanced cognitive frameworks and the complex landscape of artificial psychology using Python. Starting with an introduction to iAp, the book explores degrees of prediction and applies Fuzzy Cognitive Maps (IAP). Special focus is given to detecting implicit bias through a combination of Fuzzy Cognitive Maps and SHAP values, offering a unique perspective on artificial intelligence and psychological phenomena. The book covers forecasting in iAp, complex network analysis, and psychological graph analysis (Pga).
It delves into the intersection of deep learning and neuroimaging, as well as machine learning techniques in neuroimaging. It includes practical case studies, allowing readers to apply cutting-edge techniques to real-world psychological scenarios.
1. Chapter 1. Introduction to intricate artificial psychology - p. 1 2. Chapter 2. Intricate mind: perception, cognition, and emotion are integrated in a new paradigm for a cognitive model - p. 11 3. Chapter 3. Toward intricate thinking - p. 33 4. Chapter 4. Prediction in intricate artificial psychology - p. 49 5. Chapter 5. Detecting implicit bias using fuzzy cognitive maps - p. 83 6. Chapter 6. Forecasting in complex artificial psychology - p. 99 7. Chapter 7. Explaining neural networks in natural language - p. 121 8. Chapter 8. Complex network analysis - p. 135 9. Chapter 9. Network approach in psychology - p. 177 10. Chapter 10. Deep learning techniques in neuroimaging - p. 209 11. Chapter 11. Machine learning techniques in neuroimaging - p. 255 12. Chapter 12. Becoming a PsychoPythonista - p. 289 13. Index - p. 321
Introduction to Intricate Artificial Psychology with Python unlocks the mysteries of Intricate Artificial Psychology (iAp). This comprehensive guide takes readers through advanced cognitive frameworks and the complex landscape of artificial psychology using Python. Starting with an introduction to iAp, the book explores degrees of prediction and applies Fuzzy Cognitive Maps (IAP). Special focus is given to detecting implicit bias through a combination of Fuzzy Cognitive Maps and SHAP values, offering a unique perspective on artificial intelligence and psychological phenomena. The book covers forecasting in iAp, complex network analysis, and psychological graph analysis (Pga).
It delves into the intersection of deep learning and neuroimaging, as well as machine learning techniques in neuroimaging. It includes practical case studies, allowing readers to apply cutting-edge techniques to real-world psychological scenarios.
1. Chapter 1. Introduction to intricate artificial psychology - p. 1 2. Chapter 2. Intricate mind: perception, cognition, and emotion are integrated in a new paradigm for a cognitive model - p. 11 3. Chapter 3. Toward intricate thinking - p. 33 4. Chapter 4. Prediction in intricate artificial psychology - p. 49 5. Chapter 5. Detecting implicit bias using fuzzy cognitive maps - p. 83 6. Chapter 6. Forecasting in complex artificial psychology - p. 99 7. Chapter 7. Explaining neural networks in natural language - p. 121 8. Chapter 8. Complex network analysis - p. 135 9. Chapter 9. Network approach in psychology - p. 177 10. Chapter 10. Deep learning techniques in neuroimaging - p. 209 11. Chapter 11. Machine learning techniques in neuroimaging - p. 255 12. Chapter 12. Becoming a PsychoPythonista - p. 289 13. Index - p. 321
