Найти книгу: "Data Cleaning"

Data quality is one of the most important problems in data management, since dirty data often leads to inaccurate data analytics results and incorrect business decisions. Poor data across businesses and the U.S. government are reported to cost trillions of dollars a year. Multiple surveys show that dirty data is the most common barrier faced by data scientists. Not surprisingly, developing effective and efficient data cleaning solutions is challenging and is rife with deep theoretical and engineering problems. This book is about data cleaning, which is used to refer to all kinds of tasks and activities to detect and repair errors in the data. Rather than focus on a particular data cleaning task, we give an overview of the end-to-end data cleaning process, describing various error detection and repair methods, and attempt to anchor these proposals with multiple taxonomies and views. Specifically, we cover four of the most common and important data cleaning tasks, namely, outlier detection, data transformation, error repair (including imputing missing values), and data deduplication. Furthermore, due to the increasing popularity and applicability of machine learning techniques, we include a chapter that specifically explores how machine learning techniques are used for data cleaning, and how data cleaning is used to improve machine learning models. This book is intended to serve as a useful reference for researchers and practitioners who are interested in the area of data quality and data cleaning. It can also be used as a textbook for a graduate course. Although we aim at covering state-of-the-art algorithms and techniques, we recognize that data cleaning is still an active field of research and therefore provide future directions of research whenever appropriate.

An authoritative guide to reducing household exposure to hazardous chemicals Thousands of household products contain toxic ingredients. Today, more and more people are seeking more natural cleaning methods to reduce their exposure to harsh chemicals. From the kitchen and bath to the living room and laundry, Green Cleaning For Dummies provides readers with green solutions to every common cleaning chore. Focusing on organic, nontoxic, sustainable alternatives to conventional cleaning products, it's packed with suggestions and tips for effective cleaning, and even offers green solutions for sprucing up patios, garages, vehicles, and the exterior of a house.

With increasing demand for hygienic, self-disinfecting and contamination free surfaces, interest in developing self-cleaning protective materials and surfaces has grown rapidly in recent times. This new title comprises of invited chapters from renowned researchers in the area of self-cleaning nano-coatings and the result is a comprehensive review of current research on both hydrophobic and hydrophilic (photocatalytic effect) self-cleaning materials.

This comprehensive volume provides an in-depth discussion of the fundamentals of cleaning and surface conditioning of semiconductor applications such as high-k/metal gate cleaning, copper/low-k cleaning, high dose implant stripping, and silicon and SiGe passivation. The theory and fundamental physics associated with wet etching and wet cleaning is reviewed, plus the surface and colloidal aspects of wet processing. Formulation development practices and methodology are presented along with the applications for preventing copper corrosion, cleaning aluminum lines, and other sensitive layers. This is a must-have reference for any engineer or manager associated with using or supplying cleaning and contamination free technologies for semiconductor manufacturing. From the Reviews… «This handbook will be a valuable resource for many academic libraries. Many engineering librarians who work with a variety of programs (including, but not limited to Materials Engineering) should include this work in their collection. My recommendation is to add this work to any collection that serves a campus with a materials/manufacturing/electrical/computer engineering programs and campuses with departments of physics and/or chemistry with large graduate-level enrollment.» —Randy Wallace, Department Head, Discovery Park Library, University of North Texas