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Simulation and Inference for Stochastic Differential Equations: With R Examples (Springer Series in Statistics)
Simulation and Inference for Stochastic Differential Equations: With R Examples (Springer Series in Statistics)

This book covers a highly relevant and timely topic that is of wide interest, especially in finance, engineering and computational biology. The introductory material on simulation and stochastic differential equation is very accessible and will prove popular with many readers. While there are several recent texts available that cover...

Principles of Distributed Database Systems
Principles of Distributed Database Systems
This third edition of a classic textbook can be used to teach at the senior undergraduate and graduate levels. The material concentrates on fundamental theories as well as techniques and algorithms. The advent of the Internet and the World Wide Web, and, more recently, the emergence of cloud computing and streaming data applications, has forced...
Maximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMB
Maximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMB
This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodology, including general latent variable...
Coding the Arduino: Building Fun Programs, Games, and Electronic Projects (Technology in Action)
Coding the Arduino: Building Fun Programs, Games, and Electronic Projects (Technology in Action)
Get started with Arduino and computer coding. This book is intended for those new to the Arduino and computer coding. and looking to gain the skills to write microcontroller programs that can act on given inputs and operate electromechanical output devices. 

Coding the Arduino contains four...
Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras
Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras

Deep learning simplified by taking supervised, unsupervised, and reinforcement learning to the next level using the Python ecosystem

Key Features

  • Build deep learning models with transfer learning principles in Python
  • implement transfer learning to solve real-world research...
OpenCV 3 Computer Vision with Python Cookbook: Leverage the power of OpenCV 3 and Python to build computer vision applications
OpenCV 3 Computer Vision with Python Cookbook: Leverage the power of OpenCV 3 and Python to build computer vision applications

Recipe-based approach to tackle the most common problems in Computer Vision by leveraging the functionality of OpenCV using Python APIs

Key Features

  • Build computer vision applications with OpenCV functionality via Python API
  • Get to grips with image processing, multiple...
Jupyter Cookbook: Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more
Jupyter Cookbook: Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more

Leverage the power of the popular Jupyter notebooks to simplify your data science tasks without any hassle

Key Features

  • Create and share interactive documents with live code, text and visualizations
  • Integrate popular programming languages such as Python, R, Julia, Scala...
Python for Offensive PenTest: A practical guide to ethical hacking and penetration testing using Python
Python for Offensive PenTest: A practical guide to ethical hacking and penetration testing using Python

Your one-stop guide to using Python, creating your own hacking tools, and making the most out of resources available for this programming language

Key Features

  • Comprehensive information on building a web application penetration testing framework using Python
  • Master web...
Learn Unity ML-Agents - Fundamentals of Unity Machine Learning: Incorporate new powerful ML algorithms such as Deep Reinforcement Learning for games
Learn Unity ML-Agents - Fundamentals of Unity Machine Learning: Incorporate new powerful ML algorithms such as Deep Reinforcement Learning for games

Transform games into environments using machine learning and Deep learning with Tensorflow, Keras, and Unity

Key Features

  • Learn how to apply core machine learning concepts to your games with Unity
  • Learn the Fundamentals of Reinforcement Learning and Q-Learning and apply...
Practical Game Design: Learn the art of game design through applicable skills and cutting-edge insights
Practical Game Design: Learn the art of game design through applicable skills and cutting-edge insights

Design accessible and creative games across genres, platforms, and development realities

Key Features

  • Implement the skills and techniques required to work in a professional studio
  • Ace the core principles and processes of level design, world building, and storytelling
  • ...
Website Scraping with Python: Using BeautifulSoup and Scrapy
Website Scraping with Python: Using BeautifulSoup and Scrapy
Closely examine website scraping and data processing: the technique of extracting data from websites in a format suitable for further analysis. You'll review which tools to use, and compare their features and efficiency. Focusing on BeautifulSoup4 and Scrapy, this concise, focused book highlights common problems and suggests...
Design by Evolution: Advances in Evolutionary Design (Natural Computing Series)
Design by Evolution: Advances in Evolutionary Design (Natural Computing Series)

Evolution is Nature’s design process. The natural world is full of wonderful examples of its successes, from engineering design feats such as powered flight, to the design of complex optical systems such as the mammalian eye, to the merely stunningly beautiful designs of orchids or birds of paradise. With increasing...

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