Learn IT - Books tags estimation

Physics of Multiantenna Systems and Broadband Processing (Wiley Series in Microwave and Optical Engineering)

John Wiley & Sons, 2008

Written by three internationally known researchers, this authoritative reference on the merits of MIMO systems provides a sound theoretical basis for its practical implementation. The book also addresses the important issues related to broadband adaptive processing. Physics of Multiantenna Systems and Broadband Processing provides readers...

Building Probabilistic Graphical Models with Python

Packt Publishing, 2014

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...

Python Machine Learning Cookbook

Packt Publishing, 2016

100 recipes that teach you how to perform various machine learning tasks in the real world

About This Book

Understand which algorithms to use in a given context with the help of this exciting recipe-based guide

Learn about perceptrons and see how they are used to build neural...

A Probability Path (Modern Birkhäuser Classics)

Birkhauser, 2013

Many probability books are written by mathematicians and have the built-in bias that the reader is assumed to be a mathematician coming to the material for its beauty. This textbook is geared towards beginning graduate students from a variety of disciplines whose primary focus is not necessarily mathematics for its own sake. Instead,...

An Invitation to 3-D Vision: From Images to Geometric Models (Interdisciplinary Applied Mathematics)

Springer, 2010

This book is intended to give students at the advanced undergraduate or introductory graduate level, and researchers in computer vision, robotics and computer graphics, a self-contained introduction to the geometry of three-dimensional (3- D) vision. This is the study of the reconstruction of 3-D models of objects from a...

Big and Complex Data Analysis: Methodologies and Applications (Contributions to Statistics)

Springer, 2017

This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields. Its peer-reviewed contributions showcase recent advances in variable selection, estimation and prediction strategies for a host of useful models, as well as essential new developments in the field.

...

Kalman Filtering: Theory and Practice Using MATLAB

John Wiley & Sons, 2008

From Reviews of the First Edition

"An authentic magnum opus worth much more than its weight in gold!"
—IEEE Transactions on Automatic Control

The proven textbook on Kalman filtering—now fully updated, revised, and expanded

...

Computational Methods for Modeling of Nonlinear Systems, Volume 79 (Mathematics in Science and Engineering)

Elsevier Limited, 1971

In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems.

A number of computing techniques are considered, such as

methods of operator approximation with any given accuracy;

operator interpolation techniques including a non-Lagrange...

Product-Focused Software Process Improvement: 12th International Conference, PROFES 2011

Springer, 2011

On behalf of the PROFES Organizing Committee we are proud to present the proceedings of the 12th International Conference on Product-Focused Software Process Improvement (PROFES 2011), held in Torre Canne, Italy. Since 1999 PROFES has grown in the software engineering community and has become a premium conference that brings together...

Spatial AutoRegression (SAR) Model: Parameter Estimation Techniques (SpringerBriefs in Computer Science)

Springer, 2012

Explosive growth in the size of spatial databases has highlighted the need for spatial data analysis and spatial data mining techniques to mine the interesting but implicit spatial patterns within these large databases. Extracting useful and interesting patterns from massive geo-spatial datasets is important for many application...

Principles and Theory for Data Mining and Machine Learning (Springer Series in Statistics)

Springer, 2009

This book is a thorough introduction to the most important topics in data mining and machine learning. It begins with a detailed review of classical function estimation and proceeds with chapters on nonlinear regression, classification, and ensemble methods. The final chapters focus on clustering, dimension reduction, variable selection, and...

Mastering Machine Learning Algorithms: Expert techniques to implement popular machine learning algorithms and fine-tune your models

Packt Publishing, 2018

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...

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