The Scam List

Meet the best teen con artist team around. Boone McReedy: high school conman, smooth-talking charmer, and the idiot who just got scammed out of $15,000 of his mom's money. Darby West: ass-kicker, straight-shooter, and Boone's ex-girlfriend. Now, they must team up to save their parents' business, one con at a time. That is if they don't kill each other first. As he did in his award-winning debut, DON’T GET CAUGHT, Kurt Dinan brings laughs, twists, and heart to THE SCAM LISTS’ funny world of teen con artists, exes, and outrageous five-dollar bets.

Boone McReedy: high school conman, smooth-talking charmer, and the idiot who just got scammed out of $15,000 of his mom's money. ​Darby West: ass-kicker, straight-shooter, and Boone's ex-girlfriend. Now, they must team up to save their parents' business, one con at a time. That is if they don't kill each other first.

The Canadian edition of The Little Black Book of Scams is a compact and easy to use reference guide filled with information Canadians can use to protect themselves against a variety of common scams. It debunks common myths about scams, provides contact information for reporting a scam to the correct authority, and offers a step-by-step guide for scam victims to reduce their losses and avoid becoming repeat victims. Consumers and businesses can consult The Little Black Book of Scams to avoid falling victim to social media and mobile phone scams, fake charities and lotteries, dating and romance scams, and many other schemes used to defraud Canadians of their money and personal information.

This book includes the short stories of the three dates that Boone McReedy and Darby West go on prior to THE SCAM LIST. Here you'll read about the first cons they ever run as a team, and get hints as to why Darby's broken up with Boone before the novel begins. It'll give a you a great idea of the cons, humor, and fun that await in THE SCAM LIST.

This book will help you reduce your risk of Identity Theft not just recover after you become a victim! This book explains in detail the steps that you can take to protect yourself from ID thieves and credit criminals. Issues, from Social Security Number to Internet safety, are addressed. If you are already a victim of identity theft, it is even more important that you read this book! ID thieves are rarely caught, so the likelihood of re-victimized is high. Even if the criminal is caught, they still have your information and can use it again! You can make it more difficult for criminals to obtain and use your information! This book will teach you how.

A practical guide to avoiding the most common scams, from a fraud-fighting expert U.S. consumers lose billions of dollars each year to scam artists—and the next victim could be you. While anyone can be targeted, many victims are older. In AARP's Outsmarting the Scam Artists, renowned fraud-fighter Doug Shadel offers practical advice for consumers who want to protect their money as well as the financial assets of their parents and families. Despite the rise of scams, many people are embarrassed to admit they've been victimized. The author helps break the cycle of shame by including accounts from the people who've been scammed as well as tips from a surprising source: convicted con artists who reveal how they've defrauded people like you. Get practical tips to combat all kinds of scams, from simple lottery tickets to non-existent oil and gas deals and religious ponzi schemes Learn how to protect yourself by securing your mailbox and fraud-proofing your trash Get inside the head of sophisticated scam artists to discover how you can become the type of individual they avoid Scammers are everywhere. But with Outsmarting the Scam Artists in hand, you can protect yourself and your money.

Over 60 practical recipes on data exploration and analysis About This Book Clean dirty data, extract accurate information, and explore the relationships between variables Forecast the output of an electric plant and the water flow of American rivers using pandas, NumPy, Statsmodels, and scikit-learn Find and extract the most important features from your dataset using the most efficient Python libraries Who This Book Is For If you are a beginner or intermediate-level professional who is looking to solve your day-to-day, analytical problems with Python, this book is for you. Even with no prior programming and data analytics experience, you will be able to finish each recipe and learn while doing so. What You Will Learn Read, clean, transform, and store your data usng Pandas and OpenRefine Understand your data and explore the relationships between variables using Pandas and D3.js Explore a variety of techniques to classify and cluster outbound marketing campaign calls data of a bank using Pandas, mlpy, NumPy, and Statsmodels Reduce the dimensionality of your dataset and extract the most important features with pandas, NumPy, and mlpy Predict the output of a power plant with regression models and forecast water flow of American rivers with time series methods using pandas, NumPy, Statsmodels, and scikit-learn Explore social interactions and identify fraudulent activities with graph theory concepts using NetworkX and Gephi Scrape Internet web pages using urlib and BeautifulSoup and get to know natural language processing techniques to classify movies ratings using NLTK Study simulation techniques in an example of a gas station with agent-based modeling In Detail Data analysis is the process of systematically applying statistical and logical techniques to describe and illustrate, condense and recap, and evaluate data. Its importance has been most visible in the sector of information and communication technologies. It is an employee asset in almost all economy sectors. This book provides a rich set of independent recipes that dive into the world of data analytics and modeling using a variety of approaches, tools, and algorithms. You will learn the basics of data handling and modeling, and will build your skills gradually toward more advanced topics such as simulations, raw text processing, social interactions analysis, and more. First, you will learn some easy-to-follow practical techniques on how to read, write, clean, reformat, explore, and understand your data—arguably the most time-consuming (and the most important) tasks for any data scientist. In the second section, different independent recipes delve into intermediate topics such as classification, clustering, predicting, and more. With the help of these easy-to-follow recipes, you will also learn techniques that can easily be expanded to solve other real-life problems such as building recommendation engines or predictive models. In the third section, you will explore more advanced topics: from the field of graph theory through natural language processing, discrete choice modeling to simulations. You will also get to expand your knowledge on identifying fraud origin with the help of a graph, scrape Internet websites, and classify movies based on their reviews. By the end of this book, you will be able to efficiently use the vast array of tools that the Python environment has to offer. Style and approach This hands-on recipe guide is divided into three sections that tackle and overcome real-world data modeling problems faced by data analysts/scientist in their everyday work. Each independent recipe is written in an easy-to-follow and step-by-step fashion.

Crime is undergoing a metamorphosis. The online technological revolution has created new opportunities for a wide variety of crimes which can be perpetrated on an industrial scale, and crimes traditionally committed in an offline environment are increasingly being transitioned to an online environment. This book takes a case study-based approach to exploring the types, perpetrators and victims of cyber frauds. Topics covered include: An in-depth breakdown of the most common types of cyber fraud and scams. The victim selection techniques and perpetration strategies of fraudsters. An exploration of the impact of fraud upon victims and best practice examples of support systems for victims. Current approaches for policing, punishing and preventing cyber frauds and scams. This book argues for a greater need to understand and respond to cyber fraud and scams in a more effective and victim-centred manner. It explores the victim-blaming discourse, before moving on to examine the structures of support in place to assist victims, noting some of the interesting initiatives from around the world and the emerging strategies to counter this problem. This book is essential reading for students and researchers engaged in cyber crime, victimology and international fraud.