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Practical Statistics for Data Scientists: 50 Essential Concepts
Practical Statistics for Data Scientists: 50 Essential Concepts

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their...

Digital Signal Processing with Examples in MATLAB® (Electrical Engineering & Applied Signal Processing Series)
Digital Signal Processing with Examples in MATLAB® (Electrical Engineering & Applied Signal Processing Series)

Based on fundamental principles from mathematics, linear systems, and signal analysis, digital signal processing (DSP) algorithms are useful for extracting information from signals collected all around us. Combined with today’s powerful computing capabilities, they can be used in a wide range of application areas, including...

Data Mining Using SAS Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Data Mining Using SAS Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
Most books on data mining focus on principles and furnish few instructions on how to carry out a data mining project. Data Mining Using SAS Applications not only introduces the key concepts but also enables readers to understand and successfully apply data mining methods using powerful yet user-friendly SAS macro-call files. These methods...
5 Steps to a 5 AP Statistics, 2010-2011 Edition (5 Steps to a 5 on the Advanced Placement Examinations Series)
5 Steps to a 5 AP Statistics, 2010-2011 Edition (5 Steps to a 5 on the Advanced Placement Examinations Series)

A Perfect Plan for the Perfect Score

We want you to succeed on your AP* exam. That's why we've created this 5-step plan to help you study more effectively, use your preparation time wisely, and get your best score. This easy-to-follow guide offers you a complete review of your AP course, strategies to give you the edge on test...

Building Probabilistic Graphical Models with Python
Building Probabilistic Graphical Models with Python

Solve machine learning problems using probabilistic graphical models implemented in Python with real-world applications

About This Book

  • Stretch the limits of machine learning by learning how graphical models provide an insight on particular problems, especially in high dimension areas such as image...
Data Analysis with IBM SPSS Statistics: Implementing data modeling, descriptive statistics and ANOVA
Data Analysis with IBM SPSS Statistics: Implementing data modeling, descriptive statistics and ANOVA

Master data management & analysis techniques with IBM SPSS Statistics 24

About This Book

  • Leverage the power of IBM SPSS Statistics to perform efficient statistical analysis of your data
  • Choose the right statistical technique to analyze different types of data and build efficient...
The Variational Bayes Method in Signal Processing
The Variational Bayes Method in Signal Processing
This is the first book-length treatment of the Variational Bayes (VB) approximation in signal processing. It has been written as a self-contained, self-learning guide for academic and industrial research groups in signal processing, data analysis, machine learning, identification and control. It reviews the VB distributional approximation, showing...
Digital Signal Processing
Digital Signal Processing

Sampling - Discrete time processing of continuous-time signals, Continuous-time processing of discrete-time signals, Changing the sampling rate using discrete-time processing. Transform Analysis of LTI Systems - The frequency response of LTI systems, System functions for systems characterized by LCCD (Linear Constant Coefficient Difference)...

Sampling Algorithms (Springer Series in Statistics)
Sampling Algorithms (Springer Series in Statistics)
This book is based upon courses on sampling algorithms. After having used scattered notes for several years, I have decided to completely rewrite the material in a consistent way. The books of Brewer and Hanif (1983) and H´ajek (1981) have been my works of reference. Brewer and Hanif (1983) have drawn up an...
Computer Vision Metrics: Survey, Taxonomy, and Analysis
Computer Vision Metrics: Survey, Taxonomy, and Analysis

Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necessary background to develop intuition about why interest point detectors and feature descriptors...

Methodology of Longitudinal Surveys (Wiley Series in Survey Methodology)
Methodology of Longitudinal Surveys (Wiley Series in Survey Methodology)
Longitudinal surveys are surveys that involve collecting data from multiple subjects on multiple occasions. They are typically used for collecting data relating to social, economic, educational and health-related issues and they serve as an important tool for economists, sociologists, and other researchers.

Focusing on the design,...

Beginning Linux Programming (Linux Programming Series)
Beginning Linux Programming (Linux Programming Series)
Provided you have some previous basic exposure to C and Unix, Beginning Linux Programming delivers an excellent overview of the world of Linux development with an appealing range of essential tools and APIs.

The standout feature of Beginning Linux Programming is its wide-ranging coverage of important topics in basic Unix...

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