Home | Amazing | Today | Tags | Publishers | Years | Search 
Foundations of Machine Learning (Adaptive Computation and Machine Learning series)
Foundations of Machine Learning (Adaptive Computation and Machine Learning series)

This graduate-level textbook introduces fundamental concepts and methods in machine learning. It describes several important modern algorithms, provides the theoretical underpinnings of these algorithms, and illustrates key aspects for their application. The authors aim to present novel theoretical tools and concepts while giving concise...

Engineering Statistics
Engineering Statistics

Montgomery, Runger, and Hubele provide modern coverage of engineering statistics, focusing on how statistical tools are integrated into the engineering problem-solving process.  All major aspects of engineering statistics are covered, including descriptive statistics, probability and probability distributions, statistical test and...

Linear Mixed-Effects Models Using R: A Step-by-Step Approach (Springer Texts in Statistics)
Linear Mixed-Effects Models Using R: A Step-by-Step Approach (Springer Texts in Statistics)

Linear mixed-effects models (LMMs) are an important class of statistical models that can be used to analyze correlated data. Such data are encountered in a variety of fields including biostatistics, public health, psychometrics, educational measurement, and sociology. This book aims to support a wide range of uses for the models by applied...

Mathematics for Econometrics
Mathematics for Econometrics

This book deals with a number of mathematical topics that are of great importance in the study of classical econometrics. There is a lengthy chapter on matrix algebra, which takes the reader from the most elementary aspects to the partitioned inverses, characteristic roots and vectors, symmetric, and orthogonal and positive (semi) definite...

Smoothing Spline ANOVA Models (Springer Series in Statistics)
Smoothing Spline ANOVA Models (Springer Series in Statistics)

Nonparametric function estimation with stochastic data, otherwise known as smoothing, has been studied by several generations of statisticians. Assisted by the ample computing power in today's servers, desktops, and laptops, smoothing methods have been finding their ways into everyday data analysis by practitioners. While scores of...

Nonlinear Computer Modeling of Chemical and Biochemical Data
Nonlinear Computer Modeling of Chemical and Biochemical Data

Assuming only background knowledge of algebra and elementary calculus, and access to a modern personal computer, Nonlinear Computer Modeling of Chemical and Biochemical Data presents the fundamental basis and procedures of data modeling by computer using nonlinear regression analysis. Bypassing the need for intermediary analytical...

Mastering SQL Server 2014 Data Mining
Mastering SQL Server 2014 Data Mining

Master selecting, applying, and deploying data mining models to build powerful predictive analysis frameworks

About This Book

  • Understand the different phases of data mining, along with the tools used at each stage
  • Explore the different data mining algorithms in depth
  • Become...
Scala for Machine Learning
Scala for Machine Learning

Leverage Scala and Machine Learning to construct and study systems that can learn from data

About This Book

  • Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulation, and source code
  • Leverage your expertise in Scala...
Doing Data Science: Straight Talk from the Frontline
Doing Data Science: Straight Talk from the Frontline

Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to...

Data Science from Scratch: First Principles with Python
Data Science from Scratch: First Principles with Python

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from...

Mastering Julia
Mastering Julia

Key Features

  • Build statistical models with linear regression and analysis of variance (ANOVA)
  • Create your own modules and contribute to the Julia package system
  • Complete an extensive data science project through the entire cycle from ETL to analytics and data visualization

...

JMP 12 Specialized Models
JMP 12 Specialized Models

JMP 12 Specialized Models provides details about modeling techniques such as partitioning, neural networks, nonlinear regression, and time series analysis. Topics include the Gaussian platform, which is useful in analyzing computer simulation experiments. The book also covers the Response Screening platform, which is useful in testing the...

Result Page: 23 22 21 20 19 18 17 16 15 14 13 
©2024 LearnIT (support@pdfchm.net) - Privacy Policy