Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
GARCH Models: Structure, Statistical Inference and Financial Applications
GARCH Models: Structure, Statistical Inference and Financial Applications

Provides a comprehensive and updated study of GARCH models and their applications in finance, covering new developments in the discipline

This book provides a comprehensive and systematic approach to understanding GARCH time series models and their applications whilst presenting the most advanced results...

Linear Algebra and Probability for Computer Science Applications
Linear Algebra and Probability for Computer Science Applications

Based on the author’s course at NYU, Linear Algebra and Probability for Computer Science Applications gives an introduction to two mathematical fields that are fundamental in many areas of computer science. The course and the text are addressed to students with a very weak mathematical background. Most of the...

Probability: With Applications and R
Probability: With Applications and R

An introduction to probability at the undergraduate level

Chance and randomness are encountered on a daily basis. Authored by a highly qualified professor in the field, Probability: With Applications and R delves into the theories and applications essential to obtaining a thorough understanding of probability.

...
Reinforcement Learning with TensorFlow: A beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym
Reinforcement Learning with TensorFlow: A beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym

Leverage the power of reinforcement learning techniques to develop self-learning systems using TensorFlow

Key Features

  • Explore reinforcement learning concepts and their implementation using TensorFlow
  • Discover different problem-solving methods for reinforcement...
Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs)
Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs)
The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. “Big data,” “data science,” and “machine learning” have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science...
Guide to Medical Image Analysis: Methods and Algorithms (Advances in Computer Vision and Pattern Recognition)
Guide to Medical Image Analysis: Methods and Algorithms (Advances in Computer Vision and Pattern Recognition)
This book presents a comprehensive overview of medical image analysis. Practical in approach, the text is uniquely structured by potential applications. Features: presents learning objectives, exercises and concluding remarks in each chapter, in addition to a glossary of abbreviations; describes a range of common imaging techniques,...
Keras Reinforcement Learning Projects: 9 projects exploring popular reinforcement learning techniques to build self-learning agents
Keras Reinforcement Learning Projects: 9 projects exploring popular reinforcement learning techniques to build self-learning agents

A practical guide to mastering reinforcement learning algorithms using Keras

Key Features

  • Build projects across robotics, gaming, and finance fields, putting reinforcement learning (RL) into action
  • Get to grips with Keras and practice on real-world unstructured...
Hands-On Reinforcement Learning with Python: Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow
Hands-On Reinforcement Learning with Python: Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow

A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python

Key Features

  • Enter the world of artificial intelligence using the power of Python
  • An example-rich guide to master various RL and DRL algorithms
  • Explore...
Probability and Algorithms
Probability and Algorithms

Some of the hardest computational problems have been successfully attacked through the use of probabilistic algorithms, which have an element of randomness to them. Concepts from the field of probability are also increasingly useful in analyzing the performance of algorithms, broadening our understanding beyond that provided by the...

Markov Chains and Stochastic Stability (Cambridge Mathematical Library)
Markov Chains and Stochastic Stability (Cambridge Mathematical Library)
'This second edition remains true to the remarkable standards of scholarship established by the first edition ... it will no doubt be a very welcome addition to the literature.' Peter W. Glynn, Prologue to the Second Edition

Meyn & Tweedie is back! The bible on Markov chains in general state spaces has been brought up to
...
Domain-Specific Languages in R: Advanced Statistical Programming
Domain-Specific Languages in R: Advanced Statistical Programming

Gain an accelerated introduction to domain-specific languages in R, including coverage of regular expressions. This compact, in-depth book shows you how DSLs are programming languages specialized for a particular purpose, as opposed to general purpose programming languages. Along the way, you’ll learn to specify tasks...

Probability and Statistics for Computer Scientists
Probability and Statistics for Computer Scientists

Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling Tools
Incorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of stochastic
...

Result Page: 11 10 9 8 7 6 5 4 3 2 
©2019 LearnIT (support@pdfchm.net) - Privacy Policy