Showing results for "cha zhang"
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Ensemble Machine Learning
Methods and Applications
2012
EN
It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “b...
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IBM SPSS Modeler Cookbook
If you've already had some experience with IBM SPSS Modeler this cookbook will help you delve deeper and exploit the incredible potential of this data mining workbench. The recipes come from some of the best brains in the business.
2013
EN
If you ve already had some experience with IBM SPSS Modeler this cookbook will help you delve deeper and exploit the incredible potential of this data mining workbench. The recipes come from some of the best brains in the business.Key FeaturesGo beyond mere insight and build models than you can deploy in the day to day running of your businessSave time and effort while getting more value from your data than ever beforeLoaded with detailed step-...
Deep Learning
A Practitioner's Approach
2017
EN
Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning—especially deep neural networks—make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks.Authors Adam Gibson and Josh Patterson provide theory on deep learning before introd...
Machine Learning
An Algorithmic Perspective, Second Edition
2014
EN
Accessible
A Proven, Hands-On Approach for Students without a Strong Statistical FoundationSince the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing work on the statistical interpretations of machine learning algorithms. Unfortunately, computer science students
2013
EN
Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. This is a practical, recipe-based book, taking the reader through the hands-on steps required to set up and use PowerPivot with as little fuss as possible. This is an introductory book on PowerPivot for basic Excel users who handle lots of data and are willing to go beyond the limitations of Excel without the need to learn a new language from scratch.
2014
EN
BASIC DBA Query v.1 - 33 must know queries for DBAsFor those who want to learn database administration or are new to database administration, this query guide will help you finding basic information about your database instance.It is designed for startup DBAs and people who are preparing for interviews in database administration. The information shared in this guide can also be referred by experienced professionals while working in their daily activities.
Big Data for Chimps
A Guide to Massive-Scale Data Processing in Practice
2015
EN
Finding patterns in massive event streams can be difficult, but learning how to find them doesn’t have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. You’ll gain a practical, actionable view of big data by working with real data and real problems.Perfect for beginners, this book’s approach will also appeal to experienced practitioners who want to br...
Advanced Analytics with Spark
Patterns for Learning from Data at Scale
2017
EN
In the second edition of this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. Updated for Spark 2.1, this edition acts as an introduction to these techniques and other best practices in Spark programming.You’ll start with an introduction to Spark and its...
2015
EN
This successful textbook on predictive text mining offers a unified perspective on a rapidly evolving field, integrating topics spanning the varied disciplines of data science, machine learning, databases, and computational linguistics. Serving also as a practical guide, this unique book provides helpful advice illustrated by examples and case studies. This highly anticipated second edition has been thoroughly revised and expanded with new material on deep learning, graph models, mining so...
Building a Columnar Database on RAMCloud
Database Design for the Low-Latency Enabled Data Center
2015
EN
This book examines the field of parallel database management systems and illustrates the great variety of solutions based on a shared-storage or a shared-nothing architecture. Constantly dropping memory prices and the desire to operate with low-latency responses on large sets of data paved the way for main memory-based parallel database management systems. However, this area is currently dominated by the shared-nothing approach in order to preserve the in-memory performance advantage by pr...
Practical Data Analysis
Pandas, MongoDB, Apache Spark, and more
2016
EN
A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache SparkKey Features\[\*\] Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data\[\*\] Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images\[\*\] A hands-on guide to understanding the nature of data and how to turn i...
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- Mathematics and Statistics (R0)
2011
EN
Classic biostatistics, a branch of statistical science, has as its main focus the applications of statistics in public health, the life sciences, and the pharmaceutical industry. Modern biostatistics, beyond just a simple application of statistics, is a confluence of statistics and knowledge of multiple intertwined fields. The application demands, the advancements in computer technology, and the rapid growth of life science data (e.g., genomics data) have promoted the formation of modern b...











