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Deep Learning with Python: Learn Best Practices of Deep Learning Models with PyTorch
Deep Learning with Python: Learn Best Practices of Deep Learning Models with PyTorch
Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by...
Structured Finance Modeling with Object-Oriented VBA (Wiley Finance)
Structured Finance Modeling with Object-Oriented VBA (Wiley Finance)
Praise for STRUCTURED FINANCE MODELING with Object-Oriented VBA

"This book is an excellent and interesting integration of financial engineering, structured finance, and structured programming, and the book accomplishes this with easy-to-follow examples, using the most commonly available tools, MS VBA and spreadsheets. The author is clearly...

Data Science Fundamentals for Python and MongoDB
Data Science Fundamentals for Python and MongoDB
Build the foundational data science skills necessary to work with and better understand complex data science algorithms. This example-driven book provides complete Python coding examples to complement and clarify data science concepts, and enrich the learning experience. Coding examples include visualizations whenever appropriate....
Simulation-Based Algorithms for Markov Decision Processes (Communications and Control Engineering)
Simulation-Based Algorithms for Markov Decision Processes (Communications and Control Engineering)
Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences.  Many real-world problems modeled by MDPs have huge state and/or action spaces, giving an opening to the curse of dimensionality and so making practical...
Advances in Mathematical Modeling for Reliability
Advances in Mathematical Modeling for Reliability
Advances in Mathematical Modeling for Reliability discusses fundamental issues on mathematical modeling in reliability theory and its applications. Beginning with an extensive discussion of graphical modeling and Bayesian networks, the focus shifts towards repairable systems: a discussion about how sensitive availability calculations parameter...
Energy Trading and Risk Management: A Practical Approach to Hedging, Trading and Portfolio Diversification
Energy Trading and Risk Management: A Practical Approach to Hedging, Trading and Portfolio Diversification
A comprehensive overview of trading and risk management in the energy markets 

Energy Trading and Risk Management provides a comprehensive overview of global energy markets from one of the
...
Generalized Fractional Calculus: New Advancements and Applications (Studies in Systems, Decision and Control, 305)
Generalized Fractional Calculus: New Advancements and Applications (Studies in Systems, Decision and Control, 305)

This book applies generalized fractional differentiation techniques of Caputo, Canavati and Conformable types to a great variety of integral inequalities e.g. of Ostrowski and Opial types, etc. Some of these are extended to Banach space valued functions. These inequalities have also great impact in numerical analysis, stochastics and...

Stochastic Approximation and Recursive Algorithms and Applications (Stochastic Modelling and Applied Probability) (v. 35)
Stochastic Approximation and Recursive Algorithms and Applications (Stochastic Modelling and Applied Probability) (v. 35)

This book presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both constrained and unconstrained problems. This second edition is a thorough revision, although the main features and structure remain unchanged. It contains many additional applications and results as...

Fundamentals of Applied Probability and Random Processes
Fundamentals of Applied Probability and Random Processes
"Each chapter is broken down into small subunits, making this a useful reference book as well as a textbook. The material is presented clearly, and solved problems are included in the text." --MAA Reviews

Provides aspiring engineers with a solid introduction to probability theory and stochastic processes

...
Level Sets and Extrema of Random Processes and Fields
Level Sets and Extrema of Random Processes and Fields
Level Sets and Extrema of Random Processes and Fields discusses how to understand the properties of the level sets of paths as well as how to compute the probability distribution of its extremal values, which are two general classes of problems that arise in the study of random processes and fields and in related applications. This book...
Performance Analysis of Queuing and Computer Networks
Performance Analysis of Queuing and Computer Networks
Performance Analysis of Queuing and Computer Networks develops simple models and analytical methods from first principles to evaluate performance metrics of various configurations of computer systems and networks. It presents many concepts and results of probability theory and stochastic processes.

After an introduction to...

Stochastic Coalgebraic Logic (Monographs in Theoretical Computer Science. An EATCS Series)
Stochastic Coalgebraic Logic (Monographs in Theoretical Computer Science. An EATCS Series)

Coalgebraic logic is an important research topic in the areas of concurrency theory, semantics, transition systems and modal logics. It provides a general approach to modeling systems, allowing us to apply important results from coalgebras, universal algebra and category theory in novel ways. Stochastic systems provide important tools for...

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