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An earnest journey from heartache to heartthrob and all the emotions along the way; at once an old-fashioned love story and a cautionary tale of self-reinvention. In San Diego County, it hasn’t rained in 580 days. But for weatherman Andy Dunne, everything else is changing fast…Only a few weeks ago, he was a newly divorced, slightly overweight meteorologist for an obscure satellite radio station, hiding his secret love for a colleague, the beautiful—and very much married—Hillary Hsing. But nearly overnight, Andy has landed a new gig, flying a magic carpet in a bizarre live-action children’s TV show. So what is affable, basically decent Andy Dunne going to do now that he can do practically anything he wants? With a parade of hot moms begging for his autograph and a family that needs his help more than ever, Andy has a lot of choices. First, though, there’s this thing with Hillary, their heated text messages, a long-awaited forecast for rain – and a few other surprises he never saw coming… From the Trade Paperback edition.
Returning to England as a young widow, Annie Blake must forge a new life for herself. But how can she start? Then fun-loving Steve Calshaw dramatically enters her life and this chance encounter seems to open up a path to that new life with someone special. But Annie should know better than most that when life is going well, life has a habit of kicking back and in a bizarre twist of fate, Steve abruptly exits her life. However, when handsome, fitness instructor Jack Cassani declares he can step in and show her a good time, this may be a route to happiness. Perhaps it is - or will her love- life be derailed yet again? Set in both England where you, the reader, will enjoy the thrills of Classic Car racing and Kenya (think elephants!), No Rain Today is a gripping romance leading the reader through Annie’s tangled paths towards true love. The novel also pays tribute to the enduring power of true friendship.
DATA SCIENCE FOR RAIN CLASSIFICATION AND PREDICTION WITH PYTHON GUI by Vivian Siahaan,Rismon Hasiholan Sianipar Pdf
The dataset used in this book consists of daily weather observations from various locations in Australia spanning a 10-year period. The target variable is "RainTomorrow," which predicts whether it will rain the following day. The dataset comprises 23 attributes, including: DATE: The date of observation.; LOCATION: The name of the weather station's location.; MINTEMP: The minimum temperature in degrees Celsius.; MAXTEMP: The maximum temperature in degrees Celsius.; RAINFALL: The amount of rainfall recorded for the day in mm.; EVAPORATION: Class A pan evaporation in mm for the 24 hours until 9 am.; SUNSHINE: The number of hours of bright sunshine in a day.; WINDGUSTDIR: The direction of the strongest wind gust in the 24 hours until midnight.; WINDGUSTSPEED: The speed of the strongest wind gust in km/h in the 24 hours until midnight.; WINDDIR9AM: The direction of the wind at 9 am. The project utilizes several machine learning models, including K-Nearest Neighbor, Random Forest, Naive Bayes, Logistic Regression, Decision Tree, Support Vector Machine, Adaboost, LGBM classifier, Gradient Boosting, and XGB classifier. Three feature scaling techniques, namely raw scaling, MinMax scaling, and standard scaling, are employed. These machine learning models are utilized to analyze the weather attributes and make predictions about the occurrence of rainfall. Each model has its strengths and may perform differently based on the characteristics of the dataset. Additionally, a GUI is developed using PyQt5 to visualize cross-validation scores, predicted values versus true values, confusion matrix, learning curves, decision boundaries, model performance, scalability, training loss, and training accuracy. These visualizations within the GUI provide a comprehensive understanding of the model's performance, learning behavior, decision-making boundaries, and the quality of its predictions. Users can leverage these insights to fine-tune the model and improve its accuracy and generalization capabilities. In addition, the GUI developed using PyQt5 also includes the capability to visualize features on a year-wise and month-wise basis. This functionality allows users to explore the variations and trends in different weather attributes across different years and months. With the year-wise and month-wise visualizations, users can gain insights into the temporal patterns and trends present in the weather data. It enables them to observe how specific attributes change over time and across different seasons, providing a deeper understanding of the weather patterns and their potential influence on rainfall occurrences.
Finite Mathematics by Carla C. Morris,Robert M. Stark Pdf
Features step-by-step examples based on actual data and connects fundamental mathematical modeling skills and decision making concepts to everyday applicability Featuring key linear programming, matrix, and probability concepts, Finite Mathematics: Models and Applications emphasizes cross-disciplinary applications that relate mathematics to everyday life. The book provides a unique combination of practical mathematical applications to illustrate the wide use of mathematics in fields ranging from business, economics, finance, management, operations research, and the life and social sciences. In order to emphasize the main concepts of each chapter, Finite Mathematics: Models and Applications features plentiful pedagogical elements throughout such as special exercises, end notes, hints, select solutions, biographies of key mathematicians, boxed key principles, a glossary of important terms and topics, and an overview of use of technology. The book encourages the modeling of linear programs and their solutions and uses common computer software programs such as LINDO. In addition to extensive chapters on probability and statistics, principles and applications of matrices are included as well as topics for enrichment such as the Monte Carlo method, game theory, kinship matrices, and dynamic programming. Supplemented with online instructional support materials, the book features coverage including: Algebra Skills Mathematics of Finance Matrix Algebra Geometric Solutions Simplex Methods Application Models Set and Probability Relationships Random Variables and Probability Distributions Markov Chains Mathematical Statistics Enrichment in Finite Mathematics An ideal textbook, Finite Mathematics: Models and Applications is intended for students in fields from entrepreneurial and economic to environmental and social science, including many in the arts and humanities.
This book deals with economic theory, not methodology. It does employ certain methodological resolutions. These resolutions and the limitations they impose on the nature and the scope of the analysis are reviewed. The first resolution concerns what kind of a theory is to be discussed. The word theory may mean many things; it may mean a hypothesis put forward as an explanation of something, an idea, or a notion. In a normative sense it may mean a recommendation, a rule, or principle to be followed. In science it usually means a system of hypotheses to be accepted as an explanation of certain facts, a set of general laws, and principles. It is also used to distinguish the general principles and methods of a subject from the practice of it.The theory with which this volume is concerned is that of science. In very general terms it may be defined as a system of hypotheses, one following from another, which permits the reader to derive from known facts and predictions of other facts. If the knowledge of the fact which we predict is important for us, in the sense that it permits us to achieve better the objectives we pursue, the theory may have a practical value. This book is therefore not only a contribution to the analysis of expectations but also an introduction to a number of selected topics in economic theory.
Statistical Machine Translation by Philipp Koehn Pdf
The dream of automatic language translation is now closer thanks to recent advances in the techniques that underpin statistical machine translation. This class-tested textbook from an active researcher in the field, provides a clear and careful introduction to the latest methods and explains how to build machine translation systems for any two languages. It introduces the subject's building blocks from linguistics and probability, then covers the major models for machine translation: word-based, phrase-based, and tree-based, as well as machine translation evaluation, language modeling, discriminative training and advanced methods to integrate linguistic annotation. The book also reports the latest research, presents the major outstanding challenges, and enables novices as well as experienced researchers to make novel contributions to this exciting area. Ideal for students at undergraduate and graduate level, or for anyone interested in the latest developments in machine translation.
Cambridge O Level Mathematics: Volume 2 by Audrey Simpson Pdf
Endorsed by University of Cambridge International Examinations. Cambridge O Level Mathematics Volume 2 provides a two-year course leading to O Level examinations from University of Cambridge International Examinations in Mathematics. The book is designed to be worked through sequentially and can be used as a classroom textbook or for self-study.
Innovations in Bayesian Networks by Dawn E. Holmes Pdf
Bayesian networks currently provide one of the most rapidly growing areas of research in computer science and statistics. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. Each of the twelve chapters is self-contained. Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Graduate students since it shows the direction of current research.
Introductory Statistics for the Health Sciences by Lise DeShea,Larry E. Toothaker Pdf
Introductory Statistics for the Health Sciences takes students on a journey to a wilderness where science explores the unknown, providing students with a strong, practical foundation in statistics. Using a color format throughout, the book contains engaging figures that illustrate real data sets from published research. Examples come from many area
Sports Management as an Emerging Economic Activity by Marta Peris-Ortiz,José Álvarez-García,María de la Cruz Del Río-Rama Pdf
This book examines the sports industry as a broad business and economic sector with an enormous influence on regional economic development. Covering topics such as sports economics, financing sports organizations, sustainability management in sports, sports tourism and doping among athletes, this book provides a timely collection of research and best practices in the areas of sports management and policy. Sports activity is a rapidly growing and evolving industry, offering numerous business opportunities--from the manufacturing of sporting equipment and activity at gyms and sports centers to revenue from sporting events and sport tourism. In order for the varied businesses across the sport industry, whether public or private, to be successful, proper management strategies and policies must be in place. This includes the knowledge of the industry, strategic planning, sector analysis, quality management and sustainable (economic and environmental) use of resources. Featuring case examples from several countries, including Spain, Turkey, Uruguay, Portugal, and Italy, this volume provides international perspectives on a wide spectrum of managerial issues across this dynamic industry.
Culture and the Changing Environment by Michael J. Casimir Pdf
Today human ecology has split into many different sub-disciplines such as historical ecology, political ecology or the New Ecological Anthropology. The latter in particular has criticised the predominance of the Western view on different ecosystems, arguing that culture-specific world views and human-environment interactions have been largely neglected. However, these different perspectives only tackle specific facets of a local and global hyper-complex reality. In bringing together a variety of views and theoretical approaches , these especially commissioned essays prove that an interdisciplinary collaboration and understanding of the extreme complexity of the human-environment interface(s) is possible.
Missing and Modified Data in Nonparametric Estimation by Sam Efromovich Pdf
This book presents a systematic and unified approach for modern nonparametric treatment of missing and modified data via examples of density and hazard rate estimation, nonparametric regression, filtering signals, and time series analysis. All basic types of missing at random and not at random, biasing, truncation, censoring, and measurement errors are discussed, and their treatment is explained. Ten chapters of the book cover basic cases of direct data, biased data, nondestructive and destructive missing, survival data modified by truncation and censoring, missing survival data, stationary and nonstationary time series and processes, and ill-posed modifications. The coverage is suitable for self-study or a one-semester course for graduate students with a prerequisite of a standard course in introductory probability. Exercises of various levels of difficulty will be helpful for the instructor and self-study. The book is primarily about practically important small samples. It explains when consistent estimation is possible, and why in some cases missing data should be ignored and why others must be considered. If missing or data modification makes consistent estimation impossible, then the author explains what type of action is needed to restore the lost information. The book contains more than a hundred figures with simulated data that explain virtually every setting, claim, and development. The companion R software package allows the reader to verify, reproduce and modify every simulation and used estimators. This makes the material fully transparent and allows one to study it interactively. Sam Efromovich is the Endowed Professor of Mathematical Sciences and the Head of the Actuarial Program at the University of Texas at Dallas. He is well known for his work on the theory and application of nonparametric curve estimation and is the author of Nonparametric Curve Estimation: Methods, Theory, and Applications. Professor Sam Efromovich is a Fellow of the Institute of Mathematical Statistics and the American Statistical Association.