Exam Prep for Bundle  New Perspectives on Microsoft Access 2013  Introductory   SAM 2013 Assessment  Training  and Projects V1 0 Multi Term Printed Access Card   Microsoft Access 2013 CourseNotes Book

Exam Prep for Bundle New Perspectives on Microsoft Access 2013 Introductory SAM 2013 Assessment Training and Projects V1 0 Multi Term Printed Access Card Microsoft Access 2013 CourseNotes

  • Author : Just the Facts101
  • Publisher : Unknown
  • Release Date : 2019-08-18
  • Genre: Uncategoriezed
  • Pages : 0
  • ISBN 10 : 1538845792

Exam Prep for Bundle New Perspectives on Microsoft Access 2013 Introductory SAM 2013 Assessment Training and Projects V1 0 Multi Term Printed Access Card Microsoft Access 2013 CourseNotes Excerpt :

Your text simplified as the essential facts to prepare you for your exams. Over 2,000 higly probable test items.

Reinforcement Learning  second edition Book

Reinforcement Learning second edition

  • Author : Richard S. Sutton
  • Publisher : MIT Press
  • Release Date : 2018-11-13
  • Genre: Computers
  • Pages : 552
  • ISBN 10 : 9780262352703

Reinforcement Learning second edition Excerpt :

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.

Identifying and Managing Project Risk Book
Score: 3
From 3 Ratings

Identifying and Managing Project Risk

  • Author : Tom Kendrick
  • Publisher : AMACOM
  • Release Date : 2009-02-27
  • Genre: Business & Economics
  • Pages : 400
  • ISBN 10 : 9780814413418

Identifying and Managing Project Risk Excerpt :

Winner of the Project Management Institute’s David I. Cleland Project Management Literature Award 2010 It’s no wonder that project managers spend so much time focusing their attention on risk identification. Important projects tend to be time constrained, pose huge technical challenges, and suffer from a lack of adequate resources. Identifying and Managing Project Risk, now updated and consistent with the very latest Project Management Body of Knowledge (PMBOK)® Guide, takes readers through every phase of a project, showing them how to consider the possible risks involved at every point in the process. Drawing on real-world situations and hundreds of examples, the book outlines proven methods, demonstrating key ideas for project risk planning and showing how to use high-level risk assessment tools. Analyzing aspects such as available resources, project scope, and scheduling, this new edition also explores the growing area of Enterprise Risk Management. Comprehensive and completely up-to-date, this book helps readers determine risk factors thoroughly and decisively...before a project gets derailed.

Mathematics for Machine Learning Book
Score: 5
From 1 Ratings

Mathematics for Machine Learning

  • Author : Marc Peter Deisenroth
  • Publisher : Cambridge University Press
  • Release Date : 2020-04-23
  • Genre: Computers
  • Pages : 391
  • ISBN 10 : 9781108470049

Mathematics for Machine Learning Excerpt :

Distills key concepts from linear algebra, geometry, matrices, calculus, optimization, probability and statistics that are used in machine learning.

IBM Cognos Dynamic Query Book

IBM Cognos Dynamic Query

  • Author : Nigel Campbell
  • Publisher : IBM Redbooks
  • Release Date : 2013-09-12
  • Genre: Computers
  • Pages : 124
  • ISBN 10 : 9780738438726

IBM Cognos Dynamic Query Excerpt :

This IBM® Redbooks® publication explains how IBM Cognos® Business Intelligence (BI) administrators, authors, modelers, and power users can use the dynamic query layer effectively. It provides guidance for determining which technology within the dynamic query layer can best satisfy your business requirements. Administrators can learn how to tune the query service effectively and preferred practices for managing their business intelligence content. This book includes information about metadata modeling of relational data sources with IBM Cognos Framework Manager. It includes considerations that can help you author high-performing applications that satisfy analytical requirements of users. This book provides guidance for troubleshooting issues related to the dynamic query layer of Cognos BI. Related documents: Solution Guide : Big Data Analytics with IBM Cognos BI Dynamic Query Blog post : IBM Cognos Dynamic Query Extensibility

An Introduction to Statistical Learning Book
Score: 5
From 1 Ratings

An Introduction to Statistical Learning

  • Author : Gareth James
  • Publisher : Springer Science & Business Media
  • Release Date : 2013-06-24
  • Genre: Mathematics
  • Pages : 426
  • ISBN 10 : 9781461471387

An Introduction to Statistical Learning Excerpt :

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Sam Assessment  Training  and Projects V1 0 2013 Access Code Book

Sam Assessment Training and Projects V1 0 2013 Access Code

  • Author : Cengage Learning
  • Publisher : Unknown
  • Release Date : 2013-05-13
  • Genre: Computers
  • Pages : null
  • ISBN 10 : 1285427491

Sam Assessment Training and Projects V1 0 2013 Access Code Excerpt :

Get workplace-ready with SAM 2013, the market-leading proficiency-based assessment and training solution for Microsoft Office 2013! SAM's active, hands-on environment helps you master Microsoft Office skills and computer concepts that are essential to academic and career success! Through skill-based assessments, interactive trainings, business-centric projects, and comprehensive remediation, SAM 2013 engages you in mastering the latest Microsoft Office programs at your own pace. Computer concepts labs supplement instruction of important technology-related topics and issues through engaging simulations and interactive, auto-graded assessments. SAM is your one-stop-shop for everything you need to become tech savvy.

Machine Learning in Action Book

Machine Learning in Action

  • Author : Peter Harrington
  • Publisher : Simon and Schuster
  • Release Date : 2012-04-03
  • Genre: Computers
  • Pages : 384
  • ISBN 10 : 9781638352457

Machine Learning in Action Excerpt :

Summary Machine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification. About the Book A machine is said to learn when its performance improves with experience. Learning requires algorithms and programs that capture data and ferret out the interestingor useful patterns. Once the specialized domain of analysts and mathematicians, machine learning is becoming a skill needed by many. Machine Learning in Action is a clearly written tutorial for developers. It avoids academic language and takes you straight to the techniques you'll use in your day-to-day work. Many (Python) examples present the core algorithms of statistical data processing, data analysis, and data visualization in code you can reuse. You'll understand the concepts and how they fit in with tactical tasks like classification, forecasting, recommendations, and higher-level features like summarization and simplification. Readers need no prior experience with machine learning or statistical processing. Familiarity with Python is helpful. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside A no-nonsense introduction Examples showing common ML tasks Everyday data analysis Implementing classic algorithms like Apriori and Adaboos Table of Contents PART 1 CLASSIFICATION Machine learning basics Classifying with k-Nearest Neighbors Splitting datasets one feature at a time: decision trees Classifying with probability theory: naïve Bayes Logistic regression Support vector machines Improving classification with the AdaBoost meta algorithm PART 2 FORECASTING NUMERIC VALUES WITH REGRESSION Predict

The Psychosocial Implications of Disney Movies Book

The Psychosocial Implications of Disney Movies

  • Author : Lauren Dundes
  • Publisher : MDPI
  • Release Date : 2019-07-11
  • Genre: Philosophy
  • Pages : 246
  • ISBN 10 : 9783038978480

The Psychosocial Implications of Disney Movies Excerpt :

In this volume of 15 articles, contributors from a wide range of disciplines present their analyses of Disney movies and Disney music, which are mainstays of popular culture. The power of the Disney brand has heightened the need for academics to question whether Disney’s films and music function as a tool of the Western elite that shapes the views of those less empowered. Given its global reach, how the Walt Disney Company handles the role of race, gender, and sexuality in social structural inequality merits serious reflection according to a number of the articles in the volume. On the other hand, other authors argue that Disney productions can help individuals cope with difficult situations or embrace progressive thinking. The different approaches to the assessment of Disney films as cultural artifacts also vary according to the theoretical perspectives guiding the interpretation of both overt and latent symbolic meaning in the movies. The authors of the 15 articles encourage readers to engage with the material, showcasing a variety of views about the good, the bad, and the best way forward.

IBM IMS Solutions for Automating Database Management Book

IBM IMS Solutions for Automating Database Management

  • Author : Paolo Bruni
  • Publisher : IBM Redbooks
  • Release Date : 2014-12-09
  • Genre: Computers
  • Pages : 202
  • ISBN 10 : 9780738440231

IBM IMS Solutions for Automating Database Management Excerpt :

Over the last few years, IBM® IMSTM and IMS tools have been modernizing the interfaces to IMS and the IMS tools to bring them more in line with the current interface designs. As the mainframe software products are becoming more integrated with the Windows and mobile environments, a common approach to interfaces is becoming more relevant. The traditional 3270 interface with ISPF as the main interface is no longer the only way to do some of these processes. There is also a need to provide more of a common looking interface so the tools do not have a product-specific interface. This allows more cross product integration. Eclipse and web-based interfaces being used in a development environment, tooling using those environments provides productivity improvements in that the interfaces are common and familiar. IMS and IMS tools developers are making use of those environments to provide tooling that will perform some of the standard DBA functions. This book will take some selected processes and show how this new tooling can be used. This will provide some productivity improvements and also provide a more familiar environment for new generations DBAs. Some of the functions normally done by DBA or console operators can now be done in this eclipse-based environment by the application developers. This means that the need to request these services from others can be eliminated. This IBM Redbooks® publication examines specific IMS DBA processes and highlights the new IMS and IMS tools features, which show an alternative way to accomplish those processes. Each chapter highlights a different area of the DBA processes like: PSB creation Starting/stopping a database in an IMS system Recovering a database Cloning a set of databases

IBM Tivoli Directory Server for z OS Book

IBM Tivoli Directory Server for z OS

  • Author : Karan Singh
  • Publisher : IBM Redbooks
  • Release Date : 2011-07-07
  • Genre: Computers
  • Pages : 340
  • ISBN 10 : 9780738435725

IBM Tivoli Directory Server for z OS Excerpt :

This IBM® Redbooks® publication examines the IBM Tivoli® Directory Server for z/OS®. IBM Tivoli Directory Server is a powerful Lightweight Directory Access Protocol (LDAP) infrastructure that provides a foundation for deploying comprehensive identity management applications and advanced software architectures. This publication provides an introduction to the IBM Tivoli Directory Server for z/OS that provides a brief summary of its features and a examination of the possible deployment topologies. It discusses planning a deployment of IBM Tivoli Directory Server for z/OS, which includes prerequisites, planning considerations, and data stores, and provides a brief overview of the configuration process. Additional chapters provide a detailed discussion of the IBM Tivoli Directory Server for z/OS architecture that examines the supported back ends, discusses in what scenarios they are best used, and provides usage examples for each back end. The discussion of schemas breaks down the schema and provides guidance on extending it. A broad discussion of authentication, authorization, and security examines the various access protections, bind mechanisms, and transport security available with IBM Tivoli Directory Server for z/OS. This chapter also provides an examination of the new Password Policy feature. Basic and advanced replication topologies are also covered. A discussion on plug-ins provides details on the various types of plug-ins, the plug-in architecture, and creating a plug-in, and provides an example plug-in. Integration of IBM Tivoli Directory Server for z/OS into the IBM Workload Manager environment is also covered. This publication also provides detailed information about the configuration of IBM Tivoli Directory Server for z/OS. It discusses deploying IBM Tivoli Directory Server for z/OS on a single system, with examples of configuring the available back ends. Configuration examples are also provided for deploying the server in a Sysplex, and for both basic

Contextualizing Openness Book

Contextualizing Openness

  • Author : Leslie Chan
  • Publisher : Perspectives on Open Access
  • Release Date : 2018-04-24
  • Genre: Education
  • Pages : 280
  • ISBN 10 : 0776626663

Contextualizing Openness Excerpt :

A fascinating look at Open Science and the democratization of knowledge in international development and social transformation.

Learning Spark Book

Learning Spark

  • Author : Jules S. Damji
  • Publisher : O'Reilly Media
  • Release Date : 2020-07-16
  • Genre: Computers
  • Pages : 400
  • ISBN 10 : 9781492050018

Learning Spark Excerpt :

Data is bigger, arrives faster, and comes in a variety of formats—and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark. Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, you’ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow