Machine learning using R

Control your machine learning algorithms using test-driven development to achieve quantifiable milestonesAbout This BookBuild smart extensions to pre-existing features at work that can help maximize t

Computational Statistics and Machine Learning: A Sparse Approach focuses on using sparse algorithms in statistics and machine learning. The first part addresses the L_0 norm minimization using greedy

Road Traffic Modelling and Management: Using Statistical Monitoring and Deep Learning provides a framework for understanding and enhancing road traffic monitoring and management. It examines both the commonly used traffic analysis methodologies as well the emerging ones that use deep learning methods. The book also shows how to understand statistical models and machine learning algorithms, and how to apply them to traffic modelling, estimation, forecasting and traffic congestion monitoring. Providing both a theoretical framework along with practical technical solutions, Road Traffic Modelling and Management: Using Statistical Monitoring and Deep Learning is for researchers and practitioners who want to improve the performance of intelligent transportation systems.

Technology of Machine Tools, 8e provides state-of-the-art training for using machine tools in manufacturing technology, including up-to-date coverage of computer numerical control (CNC). It includes a

Sufficient dimension reduction is a rapidly developing research field that has wide applications in regression diagnostics, data visualization, machine learning, genomics, image processing, pattern re

"This book presents some new ideas about estimation and evaluation of the quality of software and using a standard conversion method so that lines of code from any language may be compared and be used

Timely and reliable information on natural resources, regarding their potential and limitations, is a prerequisite for sustainable development. Geospatial technologies offer immense potential in providing such information in a timely and cost-effective manner. Using orbital sensors data in conjunction with airborne and proximal sensors to generate information on soils and agricultural resources, forests, mineral resources, fossil fuel, wetlands, water resources, and marine resources, this book focuses on the advancements in technologies applicable to managing these resources. It addresses global issues like climate change and land degradation neutrality and introduces Spatial Data Infrastructure (SDI) as a mechanism for sharing geospatial data. It also provides in-depth discussion on drones, crowdsourcing, cloud computing, Internet of Things, machine learning, and their applications.Features Provides a comprehensive resource on the latest developments in geospatial technologies and the

A hands-on, code-based guide to leveraging Julia in a variety of scientific and data-driven scenarios Key Features: Augment your basic computing skills with an in-depth introduction to JuliaFocus on topic-based approaches to scientific problems and visualisationBuild on prior knowledge of programming languages such as Python, R, or C/C++Purchase of the print or Kindle book includes a free PDF eBook Book Description: Julia is a well-constructed programming language which was designed for fast execution speed by using just-in-time LLVM compilation techniques, thus eliminating the classic problem of performing analysis in one language and translating it for performance in a second.This book is a primer on Julia's approach to a wide variety of topics such as scientific computing, statistics, machine learning, simulation, graphics, and distributed computing.Starting off with a refresher on installing and running Julia on different platforms, you'll quickly get to grips with the core concept

EEG Brain Signal Classification for Epileptic Seizure Disorder Detection provides the knowledge necessary to classify EEG brain signals to detect epileptic seizures using machine learning techniques.

Learn how today’s businesses can transform themselves by leveraging real-time data and advanced machine learning analytics. This book provides prescriptive guidance for architects and develo

Get a hands-on introduction to machine learning with genetic algorithms using Python. Step-by-step tutorials build your skills from Hello World! to optimizing one genetic algorithm with another, and f

Unleash the power of computer vision with Python using OpenCVAbout This BookCreate impressive applications with OpenCV and PythonFamiliarize yourself with advanced machine learning conceptsHarness the

This book is perfect for R programmers who are interested in learning to use ggplot2 for data visualization, from the basics up to using more advanced applications, such as faceting and grouping. Sinc

Industrial Strength Empirical Modeling clearly explains the main principles of the different machine learning approaches and offers a methodology of how to integrate these techniques for successful r