Deepak K. Kanungo
Probabilistic Machine Learning for Finance and Investing: A Primer to the Next Generation of AI with Python
Probabilistic Machine Learning for Finance and Investing: A Primer to the Next Generation of AI with Python
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- More about Probabilistic Machine Learning for Finance and Investing: A Primer to the Next Generation of AI with Python
Probabilistic ML is the next generation ML framework and technology for AI-powered financial and investing systems, as it treats uncertainties and errors as features and quantifies uncertainty as probability distributions. This makes for realistic financial inferences and predictions useful for decision-making and risk management.
Format: Paperback / softback
Length: 200 pages
Publication date: 31 August 2023
Publisher: O'Reilly Media
Financial models, whether rooted in academic theories or machine learning strategies, face inherent limitations due to modeling errors. While these errors can be mitigated, they cannot be completely eradicated. Probabilistic machine learning (ML) technologies, on the other hand, are built upon a straightforward and intuitive understanding of probability and the rigorous calculus of probability theory. These systems perceive uncertainties and errors within financial and investing systems as features, rather than bugs. They quantify the uncertainty arising from imprecise inputs and outputs as probability distributions, rather than point estimates. This approach yields realistic financial inferences and predictions that are invaluable for decision-making and risk management. Moreover, probabilistic ML systems possess the capability to alert us when their inferences and predictions become outdated in the current market environment.
Probabilistic ML represents the cutting-edge ML framework and technology for AI-powered financial and investing systems. By departing from flawed statistical methodologies and adopting a broader perspective of probability as a mathematically rigorous statistical framework, it enables a more intuitive understanding of probability. This book serves as a guide, demonstrating how probabilistic ML can be leveraged to effectively quantify uncertainty and drive successful outcomes in the realm of finance and investing.
Dimension: 233 x 178 (mm)
ISBN-13: 9781492097679
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