Beyond Policy Analysis

Cengage Learning'

Authoritative and intrepid, Beyond Policy Analysis examines public policymaking in Canada with an eye to what lies beyond conventional categories and concepts. Author Leslie A. Pal explores the extent to which the world of policymaking has reacted to the increasing pressures of globalization, information technology, changing public values and cultural assumptions, citizen distrust, and decentralization and subsidiarity. His fifth edition keeps up with the hectic pace of ever-evolving governance and includes updated examples and statistical information, a greater balance between Canadian and international policy in Chapter 2, and the inclusion of a new chapter on political communication (Ch.9).

Beyond Policy Analysis: Public Issue Management in Turbulent Times

Nelson College Indigenous

A synthesis of Game Master and Players' Guide, talent show, fan forum, news/house organ, sourcebook and fun for the entire Megaverse of Palladium RPGs. Every issue, unique and informative.Palladium News.Coming Attractions.G.M. & Player tips.Optional Nightbane Morphus tables & Beyond the Supernatural O.C.C.s.How to name characters by Erick Wujcik.Knights of the Dinner Table comic strip by Blackburn.Rifts: Siege on Tolkeen - a serialized novella.A bunch of Rifts RPG stuffand a whole lot more!

The Rifter #1

Palladium Books

Features: <li>New Techno-Wizard O.C.C.s and new TW items 
</li>
<li>The Wormwood Blood Shaman and Blood Magic 
</li>
<li>Hacking &amp; Cyberjacking Across the Megaverse 
</li>
<li>KODT strip 
</li>
<li>Fan fiction and more</li>

Rifter

Steven Trustrum

Shawn Merrow

Features: <li>Systems Failure adventure &amp; Bugs 
</li>
<li>Rifts Vampires &amp; variant Necromancers 
</li>
<li>Nightbane &amp; BTS Werebeasts &amp; Monsters 
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<li>Palladium Fantasy RPG: Deep Forest &amp; Monsters 
</li>
<li>Rifts Fiction 
</li>
<li>Rifts Comic Strip</li>

The Rifter #8

Features: <li>Rifts -- Bio-Borgs. 
</li>
<li>Rifts -- The Arzno Territory &amp; Mercenaries. 
</li>
<li>Palladium Fantasy: HLS adventures. 
</li>
<li>Nightbane: The Astral Plane &amp; new O.C.C.s and powers. 
</li>
<li>Rifts Lone Star comic strip by Perez. 
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<li>Knights of the Dinner Table comic strip. 
</li>
<li>Rifts fiction &amp; serialized stories.</li>

The Rifter #9

Step by Step guide filled with real world practical examples.About This Book<ul>
<li>Get your first experience with data analysis with one of the most powerful types of analysis—time-series.</li>
<li>Find patterns in your data and predict the future pattern based on historical data.</li>
<li>Learn the statistics, theory, and implementation of Time-series methods using this example-rich guide</li>
</ul>Who This Book Is ForThis book is for anyone who wants to analyze data over time and/or frequency. A statistical background is necessary to quickly learn the analysis methods.What You Will Learn<ul>
<li>Understand the basic concepts of Time Series Analysis and appreciate its importance for the success of a data science project</li>
<li>Develop an understanding of loading, exploring, and visualizing time-series data</li>
<li>Explore auto-correlation and gain knowledge of statistical techniques to deal with non-stationarity time series</li>
<li>Take advantage of exponential smoothing to tackle noise in time series data</li>
<li>Learn how to use auto-regressive models to make predictions using time-series data</li>
<li>Build predictive models on time series using techniques based on auto-regressive moving averages</li>
<li>Discover recent advancements in deep learning to build accurate forecasting models for time series</li>
<li>Gain familiarity with the basics of Python as a powerful yet simple to write programming language</li>
</ul>In DetailTime Series Analysis allows us to analyze data which is generated over a period of time and has sequential interdependencies between the observations. This book describes special mathematical tricks and techniques which are geared towards exploring the internal structures of time series data and generating powerful descriptive and predictive insights. Also, the book is full of real-life examples of time series and their analyses using cutting-edge solutions developed in Python.
The book starts with descriptive analysis to create insightful visualizations of internal structures such as trend, seasonality and autocorrelation. Next, the statistical methods of dealing with autocorrelation and non-stationary time series are described. This is followed by exponential smoothing to produce meaningful insights from noisy time series data. At this point, we shift focus towards predictive analysis and introduce autoregressive models such as ARMA and ARIMA for time series forecasting. Later, powerful deep learning methods are presented, to develop accurate forecasting models for complex time series, and under the availability of little domain knowledge. All the topics are illustrated with real-life problem scenarios and their solutions by best-practice implementations in Python.
The book concludes with the Appendix, with a brief discussion of programming and solving data science problems using Python.Style and approachThis book takes the readers from the basic to advance level of Time series analysis in a very practical and real world use cases.

Practical Time-Series Analysis: Master Time Series Data Processing, Visualization, and Modeling using Python

Computers & Technology

PRAKASH

Programming Languages

Packt Publishing

This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses the formation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting in efficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules,. The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application. It covers the latest findings as well as directions for future research, particularly highlighting bioinformatics applications. The book is recommended for both students and practitioners working in computer science, electrical engineering, data science, system design, pattern recognition, image analysis, neural computing, social network analysis, big data analytics, computational biology and soft computing.

Granular Neural Networks, Pattern Recognition and Bioinformatics (Studies in Computational Intelligence, 712)

Computer Science

Springer

Masterguide to Maity & Ghosh's Integral Calculus Including Differential Equations

NCBA

ESSENTIALS OF BUSINESS COMMUNICATION

Sultan Chand & Sons

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Books by PAL