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.

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.

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.

Listen here for author Nancy Crisler's introduction to Discrete Mathematics Through Applications. Written specifically for high school courses, Discrete Mathematics Through Applications is designed to help you put the established NCTM Standards for Discrete Math to work in your classroom, in a way that promotes active learning, critical thinking, and fully-engaged student participation. With this text, students will see the connections among mathematical topics and real-life events and situations, while sharpening their problem solving, mathematical reasoning and communication skills. The new edition adds new topics and significantly revised exercise sets and enhanced supplements.