Machine Learning for Financial Risk Management with Python

Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use i

A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms.This book is a general introduction to machine learning that can serve as a textbook f

This book presents the latest techniques for machine learning based data analytics on IoT edge devices. A comprehensive literature review on neural network compression and machine learning accelerator

This book proposes neural networks algorithms and advanced machine learning techniques for processing nonlinear dynamic signals such as audio, speech, financial signals, feedback loops, waveform gener

This fifth edition of Fundamentals of Risk Management is a comprehensive introduction to commercial and business risk for students and risk professionals. Providing extensive coverage of the core fram

Pragmatic AI is the first truly practical guide to solving real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Writing for business professional

This book provides theoretical and practical knowledge about a methodology for evolutionary algorithm-based search strategy with the integration of several machine learning and deep learning technique

With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different ap

Critical insights for savvy financial analysts Financial Planning & Analysis and Performance Management is the essential desk reference for CFOs, FP&A professionals, investment banking profes

This publication is a practical guidebook on environmental risk assessment, especially for watershed-scale management. It highlights case studies of watershed environmental risk in Malaysia, including

The fourth edition of Essentials of Financial Management continues to provide students with a focused understanding of today’s corporate finance and financial management. This market-leading text offe

An introduction to machine learning that includes the fundamental techniques, methods, and applications Machine Learning: a Concise Introduction offers a comprehensive introduction to the core concept

Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. This book introduces theories, methods and applications of density ratio estimation, which is a newly emerging paradigm in the machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation of probability density ratios. The authors offer a comprehensive introduction of various density ratio estimators including methods via density estimation, moment matching, probabilistic classification, density fitting and density ratio fitting, as well as describing how these can be applied to machine learning. The book provides mathematical theories for density ratio estimation including parametric and non-parametric conve

Deep Learning is now ubiquitous with applied machine learning. All of the technology giants (e.g. Google, Microsoft, Apple, etc.) are focusing on deep learning based techniques for data analytics and

Learn how to solve challenging machine learning problems with Tensorflow, Google’s revolutionary new system for deep learning. If you have some background with basic linear algebra and calculus,

There are six interrelated segments to a complete financial plan: Cash & Budget Planning, Insurance & Risk Management, Tax Management, Retirement Planning, Investment Planning, and Estate Planning. Wh

This book develops a machine-learning framework for predicting economic growth. It can also be considered as a primer for using machine learning (also known as data mining or data analytics) to answer

Direct from Microsoft, this Exam Ref is the official study guide for the Microsoft 70-774 Perform Cloud Data Science with Azure Machine Learning certification exam, the second of two exams required fo

Christian Hugo Hoffmann undermines the citadel of risk assessment and management, arguing that classical probability theory is not an adequate foundation for modeling systemic and extreme risk in comp

Machine learning applications autonomously reason about data at massive scale. It's important that they remain responsive in the face of failure and changes in load. But machine learning systems are d

Systemic Risk provides readers with a wide-ranging practical guide to systemic risk in the financial system. It challenges the notion that systemic risk is exclusively about interconnectivities withi

Financial Management in the Sport Industry provides readers with an understanding of sport finance and the importance of sound financial management in the sport industry. It begins by covering finance

A practical, real-world guide for implementing enterprise risk management (ERM) programs into your organizationEnterprise risk management (ERM) is a complex yet critical issue that all companies must

This book explores the accounting and regulatory framework associated with the acquisition and disposal of financial instruments; how to determine their value; how to manage the risk connected with th

For undergraduate courses in corporate finance and financial management. Develop and begin to apply financial principles People often struggle to see how financial concepts relate to their persona

In Practical Machine Learning with H2O.ai, author Darren Cook introduces readers to H2O, an open-source machine learning package that is gaining popularity in the data science community. This concise

This FAA handbook provides tools to help pilots determine and assess each situation for the safest possible flight with the least amount of risk. Pilots who practice effective risk management have pre

This book provides an introduction to the valuation of financial instruments on equity markets. Written from the perspective of trading, risk management and quantitative research functions and written

In today’s climate the need for a closer understanding of the relationship between the two inter-related topics of risk management and finance on construction projects is becoming increasingly crucial

Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, inc

This book continues the work of the best-selling How to Measure Anything. Douglas Hubbard along with his co-author Richard Seiersen now exam the measurement of cybersecurity. There is a gold mine or quantitative learning, and unlearning, within a study of cybersecurity. This book will critique some of cybersecurity’s premier, seemingly quantitative, risk management approaches. It will be demonstrated that many of these “risk management” methods create more risk than they resolve. Questionable security risk management methods are duplicated across industries, embedded in products and largely accepted as gospel. The authors show some techniques that can be used to dramatically improve the norm. They will also show that some methods are beyond recovery and “worse than doing nothing”.

Machine learning is an exciting new way to use computers to perform tasks that require the ability to learn from experience. In order to make machine learning a reality, programmers rely on special la

Strategic financial management is a significant field in understanding of finances, revenues and organizational assets with a long term perspective. It aims at managing and allocating financial resour

The book presents the engineering aspects of risk management. The introduction to potential risks is followed by management principles, risk diagnostic, analysis and treatment followed by examples of

In a world where big data is the norm and near-real-time decisions are crucial, machine learning (ML) is a critical component of the data workflow. Machine learning systems can quickly crunch massive

Apply risk management concepts for better understandingRisk Management in Banking – Workbook is the definitive resource that makesRisk Management in Banking more accessible to both students and practi

The International Handbook of Public Financial Management is a virtual encyclopedia of public financial management, written by topmost experts, many with a background in the IMF and World Bank. It pro

By teaching you how to code machine-learning algorithms using a test-driven approach, this practical book helps you gain the confidence you need to use machine learning effectively in a business envir

This textbook is intended for a course in sport finance. Sections cover finance basics, financial management, application of financial management in sport, and financial attributes of public sector sp

This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random for