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A Primer on Quantum Computing (SpringerBriefs in Computer Science)
A Primer on Quantum Computing (SpringerBriefs in Computer Science)
This book is about quantum computing and quantum algorithms. The book starts with a chapter introducing the basic rules of quantum mechanics and how they can be used to build quantum circuits and perform computations.

Further, Grover's algorithm is presented for unstructured search discussing its consequences and
...
Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models
Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models

Explore and master the most important algorithms for solving complex machine learning problems.

Key Features

  • Discover high-performing machine learning algorithms and understand how they work in depth
  • One-stop solution to mastering supervised, unsupervised, and...
Hidden Markov Models for Time Series: An Introduction Using R (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)
Hidden Markov Models for Time Series: An Introduction Using R (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)

Reveals How HMMs Can Be Used as General-Purpose Time Series Models

Implements all methods in R
Hidden Markov Models for Time Series: An Introduction Using R applies hidden Markov models (HMMs) to a wide range of time series types, from continuous-valued, circular, and
...

Complete Guide to Digital Project Management: From Pre-Sales to Post-Production
Complete Guide to Digital Project Management: From Pre-Sales to Post-Production
Get a 360-degree view of digital project management. Learn proven best practices from case studies and real-world scenarios. A variety of project management tools, templates, models, and frameworks are covered.

This book provides an in-depth view of digital project management from initiation to execution to monitoring and
...
Python Deep Learning Projects: 9 projects demystifying neural network and deep learning models for building intelligent systems
Python Deep Learning Projects: 9 projects demystifying neural network and deep learning models for building intelligent systems

Insightful projects to master deep learning and neural network architectures using Python and Keras

Key Features

  • Explore deep learning across computer vision, natural language processing (NLP), and image processing
  • Discover best practices for the training of deep neural...
Mathematical Statistics with Resampling and R
Mathematical Statistics with Resampling and R
This book bridges the latest software applications with the benefits of modern resampling techniques

Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. This groundbreaking book shows how to apply modern resampling techniques...

Advanced Image Processing in Magnetic Resonance Imaging (Signal Processing and Communications)
Advanced Image Processing in Magnetic Resonance Imaging (Signal Processing and Communications)
Magnetic Resonance (MR) imaging produces images of the human tissues in a noninvasive manner, revealing the structure, metabolism, and function of tissues and organs. The impact of this image technique in diagnostic radiology is impressive, due to its versatility and flexibility in joining high-quality anatomical images with functional...
Software Project Estimation: Intelligent Forecasting, Project Control, and Client Relationship Management
Software Project Estimation: Intelligent Forecasting, Project Control, and Client Relationship Management
Have you been on projects where halfway down the road it seems increasingly unlikely that you will finish as desired, but you can’t put your finger on it and simply push through with a growing resentment? Have you been in meetings where scope discussions get increasingly difficult and depressing, ultimately sucking the...
Statistical Pattern Recognition
Statistical Pattern Recognition

Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions. It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval,...

Medical Image Analysis
Medical Image Analysis

The expanded and revised edition will split Chapter 4 to include more details and examples in FMRI, DTI, and DWI for MR image modalities. The book will also expand ultrasound imaging to 3-D dynamic contrast ultrasound imaging in a separate chapter.

A new chapter on Optical Imaging Modalities elaborating microscopy, confocal...

Applied Stochastic Differential Equations (Institute of Mathematical Statistics Textbooks)
Applied Stochastic Differential Equations (Institute of Mathematical Statistics Textbooks)
Stochastic differential equations are differential equations whose solutions are stochastic processes. They exhibit appealing mathematical properties that are useful in modeling uncertainties and noisy phenomena in many disciplines. This book is motivated by applications of stochastic differential equations in target tracking and medical...
Global Positioning Systems, Inertial Navigation, and Integration
Global Positioning Systems, Inertial Navigation, and Integration

An updated guide to GNSS and INS, and solutions to real-world GPS/INS problems with Kalman filtering

Written by recognized authorities in the field, this second edition of a landmark work provides engineers, computer scientists, and others with a working familiarity with the theory and contemporary...

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