Length2h 22m
About this audiobook
AI Quantitative Methods explores the essential mathematical and statistical foundations underpinning artificial intelligence, progressing through machine learning fundamentals to advanced quantitative techniques and practical applications. The book begins with foundational topics such as linear algebra, probability, optimization, and information theory, providing the rigorous tools necessary to understand AI models. It then dives into core machine learning concepts, including supervised and unsupervised learning, evaluation metrics, probabilistic models, and deep learning architectures, emphasizing the quantitative reasoning behind algorithm design and performance assessment.
The advanced section addresses specialized topics like Bayesian machine learning, time series forecasting, reinforcement learning, causal inference, and game theory, highlighting how quantitative methods facilitate robust AI solutions in complex, dynamic environments. The final part connects theory with real-world applications across natural language processing, computer vision, financial modeling, operations research, and ethics in AI. It shows how quantitative techniques optimize decision-making, improve predictive accuracy, and ensure fairness and explainability in AI systems.
Throughout, the book emphasizes detailed mathematical formulations and algorithmic insights without unnecessary introductions or summaries, targeting readers seeking deep technical understanding. By blending theory with practical examples, it equips data scientists, AI researchers, and quantitative analysts with the tools to develop, evaluate, and deploy AI systems effectively across diverse domains.
Audiobook details
GenreEducation and Learning, Self-Help
Length2 hrs 22 mins
Narrated byListen with 1,000+ voices
FormateBook with Audio
Publish dateMay 30, 2025
LanguageEnglish
Table of contents
1Part I: Foundations
2Chapter 1: Introduction to Quantitative Analysis
3Part I: Foundations
4Chapter 2: Artificial Intelligence in Finance
5Chapter 3: Mathematics and Statistics for AI Models
Show all chaptersShow less
6Chapter 4: Supervised Learning for Financial Prediction
7Chapter 7: Reinforcement Learning in Trading and Portfolio Management
8Chapter 8: Natural Language Processing for Financial Text
9Chapter 9: Generative AI in Quantitative Research
10Chapter 10: Explainable AI and Model Interpretability
11Chapter 11: AI for Risk Management and Compliance
12Chapter 12: Programming and Tools for AI-Driven Quant Models
13Chapter 13: Data Acquisition and Processing
14Chapter 14: Deployment and Productionalization of AI Models
15Chapter 15: Ethical Considerations and Future of AI in Quant
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