Description
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.- Examines how to utilize and analyze predictive models and psychological graphs- Illustrates how to apply machine learning and deep learning techniques in neuroimaging- Includes specific code examples in Python
Table of Contents
1. Introduction to intricate artificial psychology2. Intricate mind: perception, cognition, and emotion are integrated in a new paradigm for a cognitive model3. Toward intricate thinking4. Prediction in intricate artificial psychology5. Detecting implicit bias using fuzzy cognitive maps6. Forecasting in complex artificial psychology7. Explaining neural networks in natural language8. Complex network analysis9. Network approach in psychology10. Deep learning techniques in neuroimaging11. Machine learning techniques in neuroimaging12. Becoming a PsychoPythonista
